BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:America/Los_Angeles X-WR-TIMEZONE:America/Los_Angeles BEGIN:VEVENT UID:1@escience.washington.edu DTSTART:20221020T193000Z DTEND:20221021T003000Z DTSTAMP:20221020T161903Z URL:https://escience.washington.edu/events/ds-career-fair-2022/ SUMMARY:Data Science Career Fair DESCRIPTION:Please join us\, Thursday\, October 20th\, from 11:30 a.m. – 4:30 p.m. for this year’s Fall Recruiting Fair\, hosted in-person on t he UW campus! Multiple UW programs and schools are working together to cre ate this opportunity for graduate students\, postdocs\, and undergraduates working in data science to connect with companies and research labs looki ng for permanent employees and summer interns in data science positions.\n Company registration is how open!\nStudent registration will open on Octob er 5th.\nDetails:\n\n Thursday\, October 20th\, from 11:30 a.m. – 4:30 p.m.\n Located in the Husky Union Building (HUB) Ballroom – campus map here\n\nAgenda:\n\n 12 p.m. – open to PRE-REGISTERED UW graduate stu dents and postdocs from participating data science programs. Priority acce ss will be given to students who have preregistered.\n 2:30 p.m. – open to ALL current UW students and postdocs.\n Students and postdocs must  bring their Husky Card to be admitted to the event.\n\n \;\nInforma tion for Recruiters:\nThis exciting virtual event allows you the opportuni ty to connect with UW Seattle students and alumni from across campus who a re actively seeking jobs (full and/or part-time) or internships in data sc ience. Join us for this can’t-miss piece of your recruiting plan!\nEach company will be able to bring up to 5 representatives (for free) in-perso n on the day of the career fair with free parking from 9:00 am to 5:30 pm. You are welcome to come early to setup your booth\, check-in\, and enjoy your free breakfast! During the event\, feel free to take a break in our e mployer lounge room and enjoy a free lunch away from the noise of the fair . There is no cost to participate for existing Allen School Industry Affi liate partners in good standing.\nFees:\n\n Free for current Allen Schoo l Industry Affiliates Members and eScience Industry Affiliate Members\n $200 for non-profits and government (as space allows)\n $400 for other employers\n\nRegister your company here\n \; END:VEVENT BEGIN:VEVENT UID:7@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20221103T150000 DTEND;TZID=America/Los_Angeles:20221103T160000 DTSTAMP:20221031T184528Z URL:https://escience.washington.edu/events/2023-incubator-info-session/ SUMMARY:Winter 2023 Incubator Info Session DESCRIPTION:The goal of the Data Science Incubator is to enable new science by bringing together data scientists and domain scientists to work on foc used\, intensive\, collaborative projects. We invite short proposals (1-2 pages) for a remote one-quarter data-intensive research collaboration focu sing on extracting insight from large\, noisy\, and/or heterogeneous datas ets. The program is open to any faculty\, postdoc\, staff\, or student who se research can be significantly advanced by intensive collaboration with a data science expert.\n\nTo apply\, we require a short project proposal d escribing the science goals\, the relevant datasets\, and the expected tec hnical challenges.  The ideal proposal will clearly identify both the dat asets involved and the questions to be answered\, and will explain how the technical component of the project is critical to delivering exciting new findings.\n\nJoin us for a remote informational session to answer your qu estions! \nPlease RSVP here. END:VEVENT BEGIN:VEVENT UID:9@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20221206T163000 DTEND;TZID=America/Los_Angeles:20221206T173000 DTSTAMP:20221115T173626Z URL:https://escience.washington.edu/events/uwdss-xu/ SUMMARY:UW Data Science Seminar: Jing Xu DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar event on Tues day\, December 6th from 4:30 to 5:20 p.m. PDT. The seminar will feature J ing Xu\, affiliate assistant professor at the University of Washington.\n\ n\nUse this zoom link to join\n \;\n“Children’s Behavior\, Moralit y and Meaning: Re-discovering Anthropological Fieldnotes via Natural Langu age Processing Techniques”\nAbstract: Natural language processing (NLP) techniques have become increasingly popular in social sciences and humanit ies\, but the core problem of meaning interpretation requires in-depth exp ert knowledge on the particular types of texts\, the contexts regarding ho w the texts were produced\, and the local meaning systems underlying those texts. This talk features a research model of interdisciplinary collabora tion between cultural anthropology and data science\, through analyzing a unique and historically significant set of anthropological fieldnotes abou t children’s social interactions in mid-20th century rural Taiwan. In pa rticular\, naturalistic observations of children’s cooperation and confl ict in a historical context provide invaluable insights into the question of “becoming a moral person.” Combining ethnographic interpretation wi th NLP techniques\, I compare and contrast how algorithms and human-resear chers “read” children’s social interactions and pose further questio ns about sense-making\, social cognition and knowledge production. Situate d at the intersection of anthropology\, history\, data science\, and child development research\, this work has broad significance for understanding human behavior through text.\nBiography: Jing Xu is an affiliate assistan t professor at the University of Washington. Her research primarily focuse s on moral development\, education and cultural transmission in contempora ry China\, martial law-era Taiwan and cross-cultural comparative contexts. She adopts an interdisciplinary approach that puts anthropological and ps ychological theories in conversation\, combines ethnography\, experimental and computational methods\, and draws from the broad field of Chinese stu dies. She is also collaborating with psychologists to study children’s b elief-formation and revision in politically polarized contexts. Her curren t research incorporates NLP techniques and social network analysis to exam ine a rare archive of anthropological fieldnotes\, and has received fundin g awards from the Chiang Ching-kuo Foundation\, National Academy of Educat ion/Spencer Foundation and the Wenner-Gren Foundation.\nShe holds a B.A. a nd M.A. from Tsinghua University\, China\, a Ph.D. in anthropology from Wa shington University in St. Louis\, and received postdoctoral training in p sychology at the University of Washington. She is the author of The Good C hild: Moral Development in a Chinese Preschool (Stanford University Press\ , 2017). She has published peer-reviewed articles in journals spanning mul tiple disciplines such as anthropology\, psychology\, sociology\, and area studies.\n\n \;\nThe UW Data Science Seminar is an annual lecture s eries at the University of Washington that hosts scholars working across a pplied areas of data science\, such as the sciences\, engineering\, humani ties and arts along with methodological areas in data science\, such as co mputer science\, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional part ners\, governmental agencies and industry.\nThe 2022-2023 seminars will be virtual\, and are free and open to the public. END:VEVENT BEGIN:VEVENT UID:11@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20230105T163000 DTEND;TZID=America/Los_Angeles:20230105T173000 DTSTAMP:20230104T191452Z URL:https://escience.washington.edu/events/uwdss-mussmann/ SUMMARY:UW Data Science Seminar: Steve Mussmann DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar event on Thu rsday\, January 5th from 4:30 to 5:20 p.m. PDT. The seminar will feature  Steve Mussmann\, Data Science Postdoctoral Fellow at the Institute for Fou ndations of Data Science (IFDS) at the University of Washington.\n\n\nUse this zoom link to join\n \;\n"Reducing data and computational requirem ents in machine learning with data selection techniques"\n\nAbstract: Buil ding machine learning systems requires both data and computation\, which c an each require significant resources. This talk features research on tech niques in active learning and data pruning to mitigate these costs by sele cting informative data. For cases where labels for data are expensive\, su ch as medical image annotations by trained physicians\, active learning ad aptively chooses which data to label. When training extremely large models on Internet-scale datasets require weeks of computation on large clusters \, trimming away useless and redundant data\, known as data pruning\, decr eases the computational training time. This talk covers several empirical and theoretical analyses of the most popular active learning algorithm\, u ncertainty sampling\, including an NLP application where uncertainty sampl ing requires 14x less labeled data. For data pruning\, we introduce an alg orithm based on machine teaching that enjoys near-optimal theoretical guar antees and state-of-the-art results on several standard benchmark image cl assification datasets.\nBiography: Steve is an IFDS Postdoctoral Fellow in the Paul G. Allen School of Computer Science &\; Engineering at the Un iversity of Washington working with Kevin Jamieson and Ludwig Schmidt on m achine learning methods that reduce the required amount of data. He receiv ed a Ph.D. in 2021 from Stanford University in computer science advised by Percy Liang and a B.S. in 2015 from Purdue University in math\, statistic s\, and computer science.\n \;\nThe UW Data Science Seminar is an an nual lecture series at the University of Washington that hosts scholars wo rking across applied areas of data science\, such as the sciences\, engine ering\, humanities and arts along with methodological areas in data scienc e\, such as computer science\, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners\, governmental agencies and industry.\nThe 2022-2023 se minars will be virtual\, and are free and open to the public. END:VEVENT BEGIN:VEVENT UID:10@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20230123T113000 DTEND;TZID=America/Los_Angeles:20230213T140000 DTSTAMP:20221215T191833Z URL:https://escience.washington.edu/events/winter-school-2023-data-science -tools/ SUMMARY:Winter School 2023: Data Science Tools DESCRIPTION:\n\n\n\nDirector:\nJose Manuel Magallanes\, PhD\n\n Visiting P rofessor at Evans School of Public Policy and Governance\neScience Institu te Senior Data Science Fellow\n Professor of Political Science and Govern ment at Pontificia Universidad Católica del Peru (PUCP).\n Director of t he Institute for Social Analytics and Strategic Intelligence (PULSO PUCP)\ n Professor and Head of the Interdisciplinary Group for Public Policy For esight (GI3P)\,\n\nCourse Description:\nThe University of Washington eScie nce Institute offers this winter school to students and lecturers in Globa l/Public Health\, Public Policy\, Social Sciences\, Social Work\, Internat ional Relations and Business Management  who are interested in developing basic skills and knowledge of the tools used in data science.\n\nThere ar e no prerequisites to take this course and there is no credit offered. Fac ulty\, undergraduate students and graduate students are welcome to apply.\ n\nThe deadline to submit applications is January 18th.\n\n\n\nClick her e to apply\n\n\n\n \;\n\nSchedule:\n\n\nClass 1: Monday\, January 23r d (11:30 – 2:00)\nPython and R: This class will give an overview of Pyth on and R simple data structures in a comparative way (vectors\, lists\, di ctionaries\, tuples\, sets\, dataframes). This first session will  focus on differences between these languages\, and will help students with relat ed procedures such as installation and environments\, as well as user inte rfaces.\n\nClass 2: Monday\, January 30th (11:30 – 2:00)\nPython and Jup yter: This class will give an overview of Python capabilities for differen t data management processes (collection\, saving\, and  pre-processing). The output of the session will be a file to be imported into R for statist ical work.\n\nClass 3: Monday\, February 6th (11:30 – 2:00)\nR and RStud io/Posit: This class will introduce students to R programming language. I t will focus on its capabilities for statistical computing and visualizati on..\n\nClass 4: Monday\, February 13th (11:30 – 2:00)\nReproducible Env ironments: This last class will organize the work done in the previous se ssion. It will teach students how to combine R and tools like Latex/Markdo wn (for document preparation)\, Github (for organizing data repositories)\ ,  Zotero (to manage references)\, and Zenodo (to create DOIs). All og th ese combined ensure  a reproducible paper or blog post.\n\n \;\n\nOff ice hours for this course:\nPlease email to make an appointment magajm@uw .edu\n\nNote:\nClasses are offered at the eScience Studio\, there is no vi rtual participation. However\, tutoring/office hours can be virtually.\n\n This 2023 Winter School is offered free of charge thanks to the support of the eScience Institute and its funding partners. Professor Magallanes ack nowledges the material has been developed thanks to his visiting at eScie nce and Evans School at UW\, and to the work he develops at GI3P.\n\n\ n\n\n\n\n END:VEVENT BEGIN:VEVENT UID:33@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20230517T163000 DTEND;TZID=America/Los_Angeles:20230517T172000 DTSTAMP:20230503T170312Z URL:https://escience.washington.edu/events/uwdss-flaxman/ SUMMARY:UW Data Science Seminar: Abraham Flaxman DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar event on Wedn esday\, May 17th from 4:30 to 5:20 p.m. PST. The seminar will feature Abra ham D. Flaxman\, Associate Professor of Health Metrics Sciences at the UW Institute for Health Metrics and Evaluation (IHME).\n\n\nUse this zoom lin k to join\n \;\n"Introducing pseudopeople: census-scale simulated data for entity resolution"\n\nAbstract: I will introduce and demo pseudopeop le\, our new\, publicly available Python package that we hope you will use in entity resolution research and development. pseudopeople generates c ensus-scale\, simulated population data with adjustable parameters\, to re plicate key complexities from real challenges in record linkage work. Typi cal applications of entity resolution and record linkage rely on sensitive and confidential data\, and this can be a barrier to reproducible computa tional research and sometimes even to open communication about innovations and challenges. The value hypothesis of this work is that creating realis tic\, simulated data (that includes non-confidential simulated versions of sensitive fields\, like name\, address\, and date of birth) will enable m ore research in census-scale entity resolution and guide the research towa rds challenges that Census Bureau faces in practice.\nOur work builds on p revious entity resolution data projects\, such as FEBRL\, GeCO\, and SOG\, as well as our microsimulation framework\, Vivarium. We model individual people and their household\, family\, and employment relations at USA scal e\, and include simulated versions of confidential attributes like name\, address\, income\, and social security number. On top of this\, we simulat ed a range of census-relevant data collection mechanisms\, including simul ated decennial censuses\, simulated ACS and CPS surveys\, simulated tax re cords\, and simulated social security administrative data. By creating re alistic\, but non-confidential\, data which includes these attributes\, we can make entity resolution research and development easier for ourselves and others.\nBiography: Abraham D. Flaxman\, PhD\, is an Associate Profess or of Health Metrics Sciences at the Institute for Health Metrics and Eval uation (IHME) at the University of Washington. He is currently leading the development of a simulation platform to derive “what-if” results from Global Burden of Disease estimates and is engaged in software engineering and development for verbal autopsy and probabilistic record linkage. Dr. Flaxman has previously designed software tools such as DisMod-MR that IHME uses to estimate the Global Burden of Disease\, and the Bednet Stock-and- Flow Model\, which has produced estimates of insecticide-treated net cover age in sub-Saharan Africa.\nThe UW Data Science Seminar is an annual lect ure series at the University of Washington that hosts scholars working acr oss applied areas of data science\, such as the sciences\, engineering\, h umanities and arts along with methodological areas in data science\, such as computer science\, applied math and statistics. Our presenters come fro m all domain fields and include occasional external speakers from regional partners\, governmental agencies and industry.\nThe 2022-2023 seminars wi ll be virtual\, and are free and open to the public. END:VEVENT BEGIN:VEVENT UID:32@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20230519T120000 DTEND;TZID=America/Los_Angeles:20230519T150000 DTSTAMP:20230425T182723Z URL:https://escience.washington.edu/events/discovering-aiuw-2023/ SUMMARY:Discovering AI@UW 2023 DESCRIPTION:Last May\, the eScience Institute brought together partners fro m 3 Colleges and 4 Schools to launch the AI@UW Initiative\, raising the vi sibility of prominent experts in cutting edge AI methodologies and across a breadth of AI application areas.This year we invite you to attend a matc hmaking opportunity where researchers in theory and methodology will hav e the opportunity to connect with researchers from other domains.\nTo jum pstart new projects\, collaborations formed during this event will be eli gible for seed funding (~$50k per project) through a competitive proposal process.\nThe event will feature...\n\n\n A lunchtime keynote talk exemp lifying collaboration\n Lightning talks by all participants to share rese arch areas of interest\n Conversations to connect with potential collabor ators\n\nThis free event will be held in-person on Friday\, May 19th from 12:00 to 3:00 p.m. in the Husky Union Building (HUB) Room 334 on the Unive rsity of Washington's Seattle Campus. Registration is required and is lim ited to PI-eligible researchers across the 3 UW campuses. Lunch and snack s will be provided.\n\nThis event is sponsored by the UW Office of Researc h\, the Paul G. Allen School of Computer Science &\; Engineering\, the Information School\, the NSF Institute for Foundations of Data Science (IF DS)\, and the eScience Institute. If you have any questions please reach o ut to us at ai-exec@uw.edu.\n\n\nMore info here END:VEVENT BEGIN:VEVENT UID:34@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20230531T043000 DTEND;TZID=America/Los_Angeles:20230531T052000 DTSTAMP:20230525T210230Z URL:https://escience.washington.edu/events/uwdss-khoda/ SUMMARY:UW Data Science Seminar: Elham Khoda DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar event on Wedn esday\, May 31st from 4:30 to 5:20 p.m. PST. The seminar will feature Elha m E. Khoda\, Postdoctoral Scholar at the UW Department of Physics.\n\n\nUs e this zoom link to join\n \;\n"Fast Machine Learning on FPGAs for par ticle physics applications"\n\nAbstract: In particle physics\, we are expe riencing a very high raw data rate at the Large Hadron Collider (LHC)\, wh ere the protons collide at a 40 MHZ rate. It is impossible to read out and store all the data at this high rate. So\, the particle detectors around the LHC ring use an electronic hardware "trigger" system to select potenti ally interesting particle collisions for further analysis. Currently\, one out of 400 proton-proton collision events passes the hardware trigger. As the collision rate will increase by 5-7 times in the future alternative a lgorithms\, such as ML\, can be used for fast and accurate decisions.\nIn this talk\, I will highlight the potential applications of ML for hardware (ASIC or FPGA) triggers. I will discuss a method to implement the ML algo rithms on an FPGA using the hls4ml software package. hls4ml is a user-frie ndly software based on High-Level Synthesis (HLS) designed to deploy neura l network architectures on FPGAs. I will highlight my recent work on recur sive neural networks (RNN)-based and Transformer-based algorithms for trig ger applications.\nBiography: Elham E Khoda is a UW particle physics postd oc in the EPE group working with Prof. Shih-Chieh Hsu on new particle sear ches and Machine Learning algorithms for particle physics. He completed hi s Ph.D. in particle physics at the University of British Columbia\, Vancou ver\, Canada\, on “Searches for new high-mass resonances in top-antitop and di-electron final states using the ATLAS detector”. He is interested in developing ML algorithms to solve particle physics challenges. He is a major contributor to EPE's activities toward data-driven discovery with a ccelerated AI algorithms. He is working on accelerating ML inference with coprocessors like GPUs and FPGAs.\nThe UW Data Science Seminar is an annu al lecture series at the University of Washington that hosts scholars work ing across applied areas of data science\, such as the sciences\, engineer ing\, humanities and arts along with methodological areas in data science\ , such as computer science\, applied math and statistics. Our presenters c ome from all domain fields and include occasional external speakers from r egional partners\, governmental agencies and industry.\nThe 2022-2023 semi nars will be virtual\, and are free and open to the public. END:VEVENT BEGIN:VEVENT UID:40@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20230710T080000 DTEND;TZID=America/Los_Angeles:20230714T120000 DTSTAMP:20230629T210229Z URL:https://escience.washington.edu/events/a3d3-workshop/ SUMMARY:AI Methods & Infrastructure Workshop DESCRIPTION:The A3D3 Institute is hosting the High-Throughput AI Methods an d Infrastructure Workshop.\nThe purpose of this workshop is to exchange an d explore high-throughput AI tools and infrastructure across the diverse r esearch disciplines related to the A3D3 (Accelerated Artificial Intelligen ce Algorithms for Data-Driven Discovery) Institute with the goal of foster ing multi-disciplinary discussion and idea exchange. Participants will dis cuss the high-throughput AI tools\, platforms\, and challenges related to their ongoing research and work together to grow and apply their knowledge to a hackathon challenge. This is an opportunity for students\, postdocs\ , and researchers to effectively communicate research\, collaborate\, and apply AI tools in a hands-on and cross-disciplinary environment.\nLearn mo re and register here.\nParticipants must pre-register for the workshop. T here is no registration fee.\n\nThis workshop will take place over a week\ , starting with an overview on Monday of A3D3 research areas and outline o f AI methods and platforms within those research areas (neuroscience\, hig h energy physics\, multi-messenger astronomy). Participants will then have the opportunity to present posters on related research during the worksho p reception on Monday night\, and will present in two groups so they will be able to view and provide feedback on each other's posters.\n\nThe works hop will resume on Wednesday\, with the kickoff of a hackathon challenge. This will be a "kaggle-style" AI competition judging the performance and l atency of a machine learning model deployed on an FPGA (specific topic to be announced). Cross-disciplinary and multi-experience-level teams will be formed and have the opportunity to collaborate on this task on Wednesday and Thursday before presenting their progress on Friday at the closing of the workshop. Winners will be announced in a remote event at the conclusio n of the challenge in the fall. Teams will be encouraged to meet regularly to complete their project post-workshop.\n\nThere will also be lab tour v isits on Wednesday and Thursday afternoon\, respectively. END:VEVENT BEGIN:VEVENT UID:39@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20230711T173000 DTEND;TZID=America/Los_Angeles:20230711T193000 DTSTAMP:20230627T192943Z URL:https://escience.washington.edu/events/rse-meetup-0723/ SUMMARY:Seattle Research Software Engineer Meetup DESCRIPTION:Join us for the Seattle Research Software Engineer (RSE) Meetup \, a FREE event hosted and sponsored by the eScience Institute at the Un iversity of Washington.This introductory networking event is a great oppor tunity for Research Software Engineers\, developers\, and scientists in th e Seattle area to connect\, network\, and build a community of RSEs.\nRegi ster for Free Here\nWhether you're an experienced RSE or just starting out in the field\, this meetup is designed to provide a friendly and inclusiv e environment where you can meet like-minded professionals\, share your ex periences\, and expand your professional network. Our goal is to foster a supportive community of RSEs in the region and create opportunities for co llaboration and knowledge exchange.\n\nThe event will feature networking a ctivities\, icebreakers\, and interactive discussions to help you get to k now your fellow RSEs and build meaningful connections. You'll have the opp ortunity to exchange ideas\, learn from each other's experiences\, and exp lore potential collaborations in a relaxed and informal setting.\n\nThis i s just the beginning! Our future events will feature lightning talks\, dem os\, and interactive discussions on a wide variety of topics related to re search software development\, including best practices\, tools\, technique s\, and challenges faced by RSEs in various domains. We'll cover topics ra nging from programming languages\, version control\, data management\, sof tware testing\, and more. You'll have the opportunity to hear from experie nced RSEs and researchers\, learn about cutting-edge projects\, and engage in lively discussions that will help you broaden your knowledge and stay up-to-date with the latest developments in the field.\n\nDon't miss this c hance to connect with fellow RSEs\, establish new relationships\, and be p art of a growing community of Research Software Engineers in the Seattle a rea. Food and refreshments will be provided\, and there will be ample time for networking and socializing. Come join us for an evening of building p rofessional connections\, sharing insights\, and fostering collaborations! \n\nWe look forward to welcoming you to the Seattle RSE Meetup and startin g this exciting journey of building a strong RSE community in the region! Register now to secure your spot.\nThe event will be held in the WRF Data Science Studio on the UW campus\n\n[caption id="attachment_17031" align="a ligncenter" width="683"] UW Physics/Astronomy Tower (PAT): 3910 15th Avenu e NE\, 6th floor - click for interactive map[/caption]\n\n \; ATTACH;FMTTYPE=image/jpeg:https://escience.washington.edu/wp-content/uploa ds/2023/04/SSEC-white-sq.jpg END:VEVENT BEGIN:VEVENT UID:38@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20230816T143000 DTEND;TZID=America/Los_Angeles:20230816T153000 DTSTAMP:20230725T230127Z URL:https://escience.washington.edu/events/dssg23-final-presentations/ SUMMARY:Data Science for Social Good Final Presentations DESCRIPTION:Join us on Wednesday\, August 16th for the final presentations from our Data Science for Social Good (DSSG) summer program. For the past ten weeks\, two teams have been exploring how data science can be utilized to tackle real-world issues.\n\nThe presentations will be held on the UW Seattle campus in the Physics/Astronomy Auditorium A114 - view map\n\nThis is a hybrid event. Please register by selecting your mode of attendance: \n\n Remote: register for the Zoom webinar here\n In-person: register fo r the in-person event here\n\n\n"Heating Pumps in Alaska and Beyond"\nLed by Erin Trochim\, a Research Assistant Professor at the Alaska Center for Energy and Power at the University of Alaska Fairbanks. This project focus es on fine-tuning methods for assessing heat pump usage and potential in A laska\, a key strategy in decarbonization pathways that requires a compreh ensive understanding of their use and system redundancy considerations.\n" Generating regionally integrative datasets to understand groundwater insec urities in the Colorado River Basin"\nLed by Akshay Mehra\, Assistant Prof essor of UW Earth and Space Sciences\, and Sameer Shah\, Assistant Profess or of UW Environmental and Forest Sciences. This project explores the unpr ecedented water scarcity in the Colorado River Basin\, and the drivers for groundwater elevation change\, interconnected hydrological dynamics\, and potential policy interventions to support communities\, livelihoods\, and broader determinants of well-being in the basin. ATTACH;FMTTYPE=image/jpeg:https://escience.washington.edu/wp-content/uploa ds/2022/10/escience-logo.png END:VEVENT BEGIN:VEVENT UID:42@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231003T163000 DTEND;TZID=America/Los_Angeles:20231003T172000 DTSTAMP:20230905T181553Z URL:https://escience.washington.edu/events/uwdss-dssg-1/ SUMMARY:UW Data Science Seminar: 2023 DSSG Projects DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Tuesday\, October 3rd from 4:30 to 5:20 p.m. PST. The seminar will feature both proj ect groups from eScience's Data Science for Social Good (DSSG) summer prog ram. \n\n\nThis event will take place in the Physics/Astronomy Auditorium 102 (PAA A102) on the University of Washington campus.\n\n \;\n"Heati ng Pumps in Alaska and Beyond"\nAbstract: Decarbonization\, a pressing glo bal issue\, necessitates the transition from carbon-intensive power to net -zero sources. The Arctic is an area of particular concern\, where warming occurs at double the global rate and thermal energy\, primarily fossil fu el-based\, represents about 75% of energy consumption. Accurate estimation of heat pump potential\, a key strategy in decarbonization pathways\, req uires a comprehensive understanding of their use and system redundancy con siderations.\n\nThis project focuses on fine-tuning methods for assessing heat pump usage and potential in Alaska. Access to statewide building outl ines\, coupled with climate data\, will inform current and future models. These models aim to estimate the annual heating efficiency of different he at pump units\, enabling visualization of usage patterns. This analysis is essential in gauging both present and future heat pump utilization\, prov iding critical insights for efficient decarbonization strategies.\n\n  \;\n"Generating regionally integrative datasets to understand groundwater insecurities in the Colorado River Basin"\nAbstract: The Colorado River Ba sin (CRB) is experiencing unprecedented water scarcity. Arguably\, the CRB is an epicenter of North American water crises\, and a microcosm of the e nvironmental governance challenges we can expect to observe in the coming decades. Understanding the drivers for groundwater elevation change will i nform interconnected hydrological dynamics and potential policy interventi ons to support communities\, livelihoods\, and broader determinants of wel l-being in the CRB. While water insecurity in the CRB has been covered ext ensively by the media\, much of the existing focus has been on surface wat er resource decline (e.g.\, the depletion of Lake Mead). Little understand ing exists of groundwater elevation change in the CRB\, and more important ly\, policy interventions that can support the integrative management of s urface and groundwater (i.e.\, conjunctive water governance). This project will enhance the study of groundwater change dynamics in geographies expe riencing significant water-related stressors.\n\n \;\nThe UW Data Sci ence Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science\, such as the sciences\, engineering\, humanities and arts along with methodologica l areas in data science\, such as computer science\, applied math and stat istics. Our presenters come from all domain fields and include occasional external speakers from regional partners\, governmental agencies and indus try.\nThe 2022-2023 seminars will be held in person\, and are free and ope n to the public. LOCATION:Physics/Astronomy Auditorium A102\, 3910 15th Ave NE\, Seattle\, W A\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, United States;X-APPLE-RADIUS=100;X-TITLE=Physics/Astronomy Auditori um A102:geo:0,0 END:VEVENT BEGIN:VEVENT UID:48@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231010T163000 DTEND;TZID=America/Los_Angeles:20231010T172000 DTSTAMP:20231006T174228Z URL:https://escience.washington.edu/events/uwdss-teblunthuis/ SUMMARY:UW Data Science Seminar: Nathan TeBlunthuis DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Tuesday\, October 10th from 4:30 to 5:20 p.m. PST. The seminar will feature Nathan T eBlunthuis\, a Postdoctoral Research Fellow at the Information School at t he University of Michigan. \n\n\nThis event will take place in the Physic s/Astronomy Auditorium 102 (PAA A102) on the University of Washington camp us.\n\n \;\n"Misclassification in Automated Content Analysis Causes Bi as in Regression. Can We Fix It? Yes We Can!"\nAbstract: Automated classif iers (ACs)\, often built via supervised machine learning (SML)\, can categ orize large\, statistically powerful samples of data ranging from text to images and video. They have become widely popular measurement devices in c omputational social science and related fields. Despite this popularity\, even highly accurate classifiers make errors that cause misclassification bias and misleading results when input to downstream statistical analyses —unless such analyses account for these errors. As we show in a systemat ic literature review of SML applications\,  scholars largely ignore miscl assification bias.\n\nIn principle\, existing statistical methods can use "gold standard" validation data\, such as that created by human annotators \, to correct misclassification bias. We introduce and test such methods\, including a new method we design and implement in the R package "misclass ification models"\, via Monte Carlo simulations designed to reveal each me thod's limitations\, which we also release. Based on our results\, we reco mmend our new error correction method as it is versatile and efficient. In sum\, automated classifiers\, even those below common accuracy standards or those making systematic misclassifications\, can be useful for measurem ent with careful study design and appropriate error correction methods.\n\ nBio: Dr. Nathan TeBlunthuis is a Postdoctoral Research Fellow in the Info rmation School at the University of Michigan. He was previously at the Dep artment of Communication Studies at Northwestern University and completed his PhD in Communication at the University of Washington. He is computatio nal social scientist who studies how collective action is organized in pro jects like Wikipedia\, online communities like Reddit\, and social movemen ts. An important part of his work is to improve the measurement of meanin gful communication behaviors from unstructured data such as text and multi media.\nThe UW Data Science Seminar is an annual lecture series at the U niversity of Washington that hosts scholars working across applied areas o f data science\, such as the sciences\, engineering\, humanities and arts along with methodological areas in data science\, such as computer science \, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners\, governm ental agencies and industry.\nThe 2022-2023 seminars will be held in perso n\, and are free and open to the public. LOCATION:Physics/Astronomy Auditorium A102\, 3910 15th Ave NE\, Seattle\, W A\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, United States;X-APPLE-RADIUS=100;X-TITLE=Physics/Astronomy Auditori um A102:geo:0,0 END:VEVENT BEGIN:VEVENT UID:53@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231023T100000 DTEND;TZID=America/Los_Angeles:20231023T110000 DTSTAMP:20231020T171742Z URL:https://escience.washington.edu/events/hacking-the-academy-the-adoptio n-of-open/ SUMMARY:Hacking the Academy: The Adoption of Open DESCRIPTION:In recognition of International Open Access Week\, the UW Libra ries’ Open Scholarship Commons is hosting “Hacking the Academy: The Ad option of Open” on Monday\, October 23rd from 10:00 to 11:00 a.m. over z oom. \n\nThe discussion will explore the theme of “community over commer cialization” and provide an opportunity to examine the successes and cha llenges of adopting open practices in software development\, open educatio n\, open data\, and new funding models to support this work. The event is part of OSC’s Hacking the Academy program series\, which looks at new wa ys in which research is produced\, shared\, archived\, and reused. \nGet the zoom info here.\nPanelists:\n\n Ashley Farley\, Program Officer of Kn owledge &\; Research Services\, Bill &\; Melinda Gates Foundation\n Vani Mandava\, Head of Engineering\, eScience Institute’s Scientific So ftware Engineering Center\, University of Washington\n Jenny Muilenburg\, Research Data Services Librarian\, University of Washington Libraries\n Lauren Ray\, Open Education Librarian\, University of Washington Libraries \n END:VEVENT BEGIN:VEVENT UID:49@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231024T163000 DTEND;TZID=America/Los_Angeles:20231024T172000 DTSTAMP:20231020T174647Z URL:https://escience.washington.edu/events/uwdss-perkovic/ SUMMARY:UW Data Science Seminar: Ema Perkovic DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Tuesday\, October 24th from 4:30 to 5:20 p.m. PST. The seminar will feature Ema Perk ovic\, UW Assistant Professor of Statistics. \n\n\nThis event will take p lace in the Physics/Astronomy Auditorium 102 (PAA A102) on the University of Washington campus.\n\n \;\n"Identifying and estimating causal effec ts with incomplete causal information"\nAbstract: Questions of cause and e ffect are ideally answered by intervening in a system through a randomized controlled experiment. However\, these experiments can often be costly\, time-consuming\, unethical\, or impossible to conduct. On the other hand\, observational data and specific domain or background knowledge may still be available. In this talk\, we consider how partial knowledge of causal r elationships can be combined with observational data to assess a causal ef fect while providing efficient estimators in certain settings.Suppose the causal system can be represented by a directed acyclic graph (DAG) encodin g causal relationships. This causal DAG is a priori unknown to us. Instead \, we have access to a class of potential causal DAGs representing the sam e set of observed conditional independencies and background knowledge. We present a necessary and sufficient graphical criterion to uniquely identif y a causal effect given such a class. When the causal effect cannot be uni quely identified given the class of possible graphical models\, we conside r the identification of a set of possible total causal effects and devise a minimal and complete approach to solving this problem. This result resol ves an issue with existing methods\, which often report possible total eff ects with duplicates\, namely those numerically distinct due to sampling v ariability but causally identical. Next\, for a causal effect that is iden tified from the partial knowledge of the causal relationships\, we devise an estimator based on recursive least squares. Under the linearity of the causal system\, this estimator consistently estimates the causal effect wh ile achieving a minimal asymptotic variance among a broad class of establi shed estimators. We conclude the presentation by discussing further resear ch directions.\n\nBio: Emilija Perkovic joined the Department of Statisti cs at the University of Washington in Autumn 2018 as an Acting Assistant P rofessor and was promoted to a tenure-track Assistant Professor role in Au tumn 2020.  Before coming to UW\, she completed a Ph.D. in Statistics at ETH Zürich in 2018 under the supervision of Professor Marloes Maathuis\, an M.Sc. in Statistics from ETH Zürich in 2014\, and a B.Sc. in Mathemati cs from the University of Belgrade in 2012.  Her research interests are f ocused on causal inference from the perspective of graphical models. A lar ge part of her Ph.D. thesis was on causal inference through covariate adju stment. She hopes to learn some new perspectives on causal inference while she is here.\n\n \;\nThe UW Data Science Seminar is an annual lectu re series at the University of Washington that hosts scholars working acro ss applied areas of data science\, such as the sciences\, engineering\, hu manities and arts along with methodological areas in data science\, such a s computer science\, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners\, governmental agencies and industry.\nThe 2022-2023 seminars wil l be held in person\, and are free and open to the public. LOCATION:Physics/Astronomy Auditorium A102\, 3910 15th Ave NE\, Seattle\, W A\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, United States;X-APPLE-RADIUS=100;X-TITLE=Physics/Astronomy Auditori um A102:geo:0,0 END:VEVENT BEGIN:VEVENT UID:52@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231027T090000 DTEND;TZID=America/Los_Angeles:20231027T100000 DTSTAMP:20231023T181056Z URL:https://escience.washington.edu/events/incubator-2024-info1/ SUMMARY:Data Science Incubator 2024 Q&A DESCRIPTION:eScience's Data Science Incubator program enables new science by bringing together data scientists and domain scientists to work on focu sed\, intensive\, collaborative projects. Our team of data scientists prov ides expertise in state-of-the-art technology and methods in statistics an d machine learning\, data manipulation and analytics at all scales\, cloud and cluster computing\, software design and engineering\, visualization\, and other topics. The program is open to any faculty\, postdoc\, staff\, or student whose research can be significantly advanced by intensive colla boration with a data science expert.\n\nWe invite short proposals (1-2 pag es) for a remote one-quarter data-intensive research collaboration focusin g on extracting insight from large\, noisy\, or heterogeneous datasets. To apply\, we require a short project proposal describing the science goals\ , the relevant datasets\, and the expected technical challenges.\n\nImport ant dates for the 2024 program:\n\n Applications for the 2024 program are due November 14\, 2023\n Selected projects will be announced December 12 th\, 2023\n The program will run January 4- March 8th\, 2024\n\nThis info session will be offered over zoom.\n\n Get the zoom info here\n END:VEVENT BEGIN:VEVENT UID:54@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231106T130000 DTEND;TZID=America/Los_Angeles:20231106T140000 DTSTAMP:20231031T165937Z URL:https://escience.washington.edu/events/incubator-2024-info2/ SUMMARY:Data Science Incubator 2024 Q&A DESCRIPTION:eScience's Data Science Incubator program enables new science by bringing together data scientists and domain scientists to work on focu sed\, intensive\, collaborative projects. Our team of data scientists prov ides expertise in state-of-the-art technology and methods in statistics an d machine learning\, data manipulation and analytics at all scales\, cloud and cluster computing\, software design and engineering\, visualization\, and other topics. The program is open to any faculty\, postdoc\, staff\, or student whose research can be significantly advanced by intensive colla boration with a data science expert.\n\nWe invite short proposals (1-2 pag es) for a one-quarter data-intensive research collaboration focusing on ex tracting insight from large\, noisy\, or heterogeneous datasets. To apply\ , we require a short project proposal describing the science goals\, the r elevant datasets\, and the expected technical challenges.\n\nImportant dat es for the 2024 program:\n\n Applications for the 2024 program are due No vember 14\, 2023\n Selected projects will be announced December 12th\, 20 23\n The program will run January 4- March 8th\, 2024\n\nThis info sessio n will be offered both remotely and in person in the WRF Data Science Stud io.\n\n View the location on Google Maps\n Get the zoom info here\n LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:55@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231107T170000 DTEND;TZID=America/Los_Angeles:20231107T190000 DTSTAMP:20231024T170758Z URL:https://escience.washington.edu/events/zarr-meetup/ SUMMARY:Seattle Zarr Meetup DESCRIPTION:Join us for the Seattle Zarr Meetup on November 7th\, 2023\, a new forum created for local Zarr users to connect\, collaborate\, and exch ange insights. Whether you're an experienced Zarr user or just starting ou t\, this event is designed to benefit you. Zarr is a community project to develop specifications and software for storage of large N-dimensional typ ed arrays\, also commonly known as tensors.\nRegister for the meetup here\ nGoals:\n\n Create a forum for Seattle-based Zarr users to meet each othe r and share their insights.\n Foster collaboration and knowledge exchange across different disciplines that use Zarr.\n Introduce new users to the key features and use cases of Zarr.\n Get feedback from participants on goals of a Zarr extension focused sprint to take place in Seattle in early 2024.\n\nView the full agenda LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:51@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231109T140000 DTEND;TZID=America/Los_Angeles:20231109T160000 DTSTAMP:20231011T194844Z URL:https://escience.washington.edu/events/software-workshop-sequence-to-d iagnostic-seq2dx/ SUMMARY:Software Workshop: Sequence to Diagnostic (Seq2Dx) DESCRIPTION:Seq2Dex-Accelerating Genetic Assay Development for Nature Conse rvation and Neglected Diagnostics ATTACH;FMTTYPE=image/jpeg:https://escience.washington.edu/wp-content/uploa ds/2023/10/Seq2Dx-e1697647001668.png LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:56@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231114T163000 DTEND;TZID=America/Los_Angeles:20231114T172000 DTSTAMP:20231030T220343Z URL:https://escience.washington.edu/events/uwdss-mireshghallah/ SUMMARY:UW Data Science Seminar: Niloofar Mireshghallah DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Tuesday\, November 14th from 4:30 to 5:20 p.m. PST. The seminar will feature Niloofa r Mireshghallah\, a Postdoctoral Scholar with the UW Allen Center for Comp uter Science &\; Engineering. \n\n\nThis event will take place in the Physics/Astronomy Auditorium 102 (PAA A102) on the University of Washingto n campus.\n\n \;\n"Privacy Auditing and Protection in Large Language M odels"\nAbstract: Large language Models (LLMs\, e.g.\, GPT-3\, OPT\, TNLG\ ,…) are shown to have a remarkably high performance on standard benchmar ks\, due to their high parameter count\, extremely large training datasets \, and significant compute. Although the high parameter count in these mod els leads to more expressiveness\, it can also lead to higher memorization \, which\, coupled with large unvetted\, web-scraped datasets can cause di fferent negative societal and ethical impacts such as leakage of private\, sensitive information and generation of harmful text. In this talk\, we w ill go over how these issues affect the trustworthiness of LLMs\, and zoom in on how we can measure the leakage and memorization of these models\, a nd mitigate it through differentially private training. Finally we will di scuss what it would actually mean for LLMs to be privacy preserving\, and what are the future research directions on making large models trustworthy .\n\nBiography: Niloofar Mireshghallah is a post-doctoral scholar at the P aul G. Allen Center for Computer Science &\; Engineering at University of Washington. She received her Ph.D. from the CSE department of UC San Di ego in 2023. Her research interests are Trustworthy Machine Learning and N atural Language Processing. She is a recipient of the National Center for Women &\; IT (NCWIT) Collegiate award in 2020 for her work on privacy-p reserving inference\, a finalist of the Qualcomm Innovation Fellowship in 2021 and a recipient of the 2022 Rising star in Adversarial ML award.\n\n& nbsp\;\nThe UW Data Science Seminar is an annual lecture series at the U niversity of Washington that hosts scholars working across applied areas o f data science\, such as the sciences\, engineering\, humanities and arts along with methodological areas in data science\, such as computer science \, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners\, governm ental agencies and industry.\nThe 2022-2023 seminars will be held in perso n\, and are free and open to the public. LOCATION:Physics/Astronomy Auditorium A102\, 3910 15th Ave NE\, Seattle\, W A\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, United States;X-APPLE-RADIUS=100;X-TITLE=Physics/Astronomy Auditori um A102:geo:0,0 END:VEVENT BEGIN:VEVENT UID:57@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231128T163000 DTEND;TZID=America/Los_Angeles:20231128T172000 DTSTAMP:20231106T174104Z URL:https://escience.washington.edu/events/uwdss-garyfallidis/ SUMMARY:UW Data Science Seminar: Eleftherios Garyfallidis DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Tuesday\, November 28th from 4:30 to 5:20 p.m. PST. The seminar will feature Dr. Ele ftherios Garyfallidis\, an Associate Professor of Intelligent Systems Engi neering (ISE) at Indiana University. \n\n\nThis event will take place in the Physics/Astronomy Auditorium 102 (PAA A102) on the University of Washi ngton campus.\n\n \;\n"AI breakthroughs for pre-processing structural and diffusion MRI data"\nAbstract: During my talk I will focus on two nove l approaches for segmentation and denoising.\nSegmentation: Brain extracti on is a computational necessity for researchers using brain imaging data. However\, the complex structure of the interfaces between the brain\, meni nges and human skull have not allowed a highly robust solution to emerge. While previous methods have used machine learning with structural and geom etric priors in mind\, with the development of Deep Learning (DL)\, there has been an increase in Neural Network based methods. Most proposed DL mod els focus on improving the training data despite the clear gap between gro ups in the amount and quality of accessible training data between. We prop ose an architecture we call Efficient V-net with Additional Conditional Ra ndom Field Layers (EVAC+). EVAC+ has 3 major characteristics: (1) a smart augmentation strategy that improves training efficiency\, (2) a unique way of using a Conditional Random Fields Recurrent Layer that improves accura cy and (3) an additional loss function that fine-tunes the segmentation ou tput. We compare our model to state-of-the-art non-DL and DL methods.\nDen oising: Patch2Self (P2S)\, which performs self-supervised denoising of dMR I data using the statistical independence of noise\, has previously shown state-of-the-art results by performing a series of regression analyses on the so-called Casorati matrix. P2S however is resource intensive\, both in terms of running time and memory usage. This work exploits the redundancy imposed by P2S to alleviate its performance issues and inspect regions th at influence the noise disproportionately. Specifically\, this study makes a two-fold contribution: (1) We present Patch2Self2 (P2S2)\, a method tha t uses matrix sketching to perform self-supervised denoising. By solving a sub-problem on a smaller sub-space\, so called\, coreset\, we show how P2 S2 can yield a significant speedup in training time while using less memor y. (2) We show how the so-called statistical leverage scores can be used t o interpret the denoising of dMRI data\, a process that was traditionally treated as a black-box. Our experiments are conducted on simulated and rea l data and clearly demonstrate that P2S2 does not lead to any loss in deno ising quality\, while providing significant speedup and improved memory us age by training on only a small fraction of the data.\nBiography: Dr. Gary fallidis holds the position of Associate Professor of Intelligent Systems Engineering (ISE) at Indiana University (IU). Prof. Garyfallidis works on the interface between machine learning\, medical imaging and engineering v isualization. He is the inventor of multiple ground breaking algorithms in cluding QuickBundles. QuickBundles was the first fast and unsupervised alg orithm in neuroimaging for grouping tractographies using streamlines. Prof . Garyfallidis is the inventor of SLR. SLR is the most accurate method for affinely registering bundles or tractograms. His research has been fundam ental in understanding the challenges of brain tractography. Due to a meth od called RecoBundles\, in 2015 Garyfallidis enabled the evaluation of tra ctographies in data with distortions. Prof. Garyfallidis is the founder an d lead engineer of DIPY. The pioneering work that Dr. Garyfallidis started and is today championed by his graduate students. See for example his lab s work on Patch2Self denoising\, EVAC+ and Bundle Analytics (BUAN). Prof. Garyfallidis is organizing yearly workshops (see DIPY workshops) to train faculty and students to use the latest methods in neuroimaging.\n\n \; \nThe UW Data Science Seminar is an annual lecture series at the Univers ity of Washington that hosts scholars working across applied areas of data science\, such as the sciences\, engineering\, humanities and arts along with methodological areas in data science\, such as computer science\, app lied math and statistics. Our presenters come from all domain fields and i nclude occasional external speakers from regional partners\, governmental agencies and industry.\nThe 2023-2024 seminars will be held in person\, an d are free and open to the public. LOCATION:Physics/Astronomy Auditorium A102\, 3910 15th Ave NE\, Seattle\, W A\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, United States;X-APPLE-RADIUS=100;X-TITLE=Physics/Astronomy Auditori um A102:geo:0,0 END:VEVENT BEGIN:VEVENT UID:58@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231205T163000 DTEND;TZID=America/Los_Angeles:20231205T172000 DTSTAMP:20231121T173338Z URL:https://escience.washington.edu/events/uwdss-phuong/ SUMMARY:UW Data Science Seminar: Jim Phuong DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Tuesday\, D ecember 5th from 4:30 to 5:20 p.m. PST. The seminar will feature Jimmy Phu ong\, MSPH\, PhD\, who is Acting Assistant Professor of UW Biomedical and Health Informatics\; lead research data scientist at UW Medicine Research IT\; and staff research data scientist\, Research core at Harborview Injur y Prevention and Research Center.\n\n\nThis event will take place in the P hysics/Astronomy Auditorium 102 (PAA A102) on the University of Washington campus. This will be the final seminar of the Fall 2023 Quarter. \n\n&nb sp\;\n"Population health research &\; research data sharing in national research consortia"\nAbstract: Health systems are uniquely positioned to survey the health of their patient population\, including the effects of natural hazards\, disaster disruptions\, and public health emergencies.  Health systems are an integral part of biomedical research consortia\, whe re data sharing supports data-driven research and iterative quality impr ovements to the data from each health system.  Apart from clinical outco mes\, health systems are gradually increasing their focus upon collecting and addressing gaps in understanding Social Determinants of Health (or Soc ial Drivers of Health\, SDoH) and their dynamic role in maintaining health and wellness.  This includes integrating patient-level information as we ll as place-based information integrated from geocoding and secondary use of spatial-temporal datasets. In this talk\, I will discuss the nexus of environmental health\, disaster management and population health research\ , and biomedical informatics research.  I will also discuss the direction s from health system preparedness\, the broader implications towards resea rch data sharing and research consortia with a precision medicine focus\, and the analytical capacities needed for research with multiple data types in cloud infrastructure. \n\nBio: Dr. Jimmy Phuong is an Acting Assist ant Professor in University of Washington (UW) Biomedical Informatics and Medical Education (BIME). He also serves as Lead Research Data Scientist U W Medicine Research IT and Harborview Injury Prevention Research Center an d has been a co-champion for the NIH National COVID-19 Cohort Collaborativ e (N3C) Social Determinants of Health (SDoH) Domain team.  Dr. Phuong is a UW BIME PhD alumni of Dr. Sean Mooney's lab. Prior to joining Universi ty of Washington\, Dr. Phuong has been a bioinformatics analyst and resea rch fellow at the US Environmental Protection Agency (US EPA) National Cen ter for Computational Toxicology.  Dr. Phuong currently focuses on integr ating clinical and spatial-temporal data types to support data engineering and research data science applications.  His research currently touches on the secondary use and integration of electronic health records\, disast er preparedness and injury prevention research\, Social Determinants of He alth\, including research consortial data engineering to advance areas of population health and precision medicine research.\nThe UW Data Science Se minar is an annual lecture series at the University of Washington that ho sts scholars working across applied areas of data science\, such as the sc iences\, engineering\, humanities and arts along with methodological areas in data science\, such as computer science\, applied math and statistics. Our presenters come from all domain fields and include occasional externa l speakers from regional partners\, governmental agencies and industry.\nT he 2023-2024 seminars will be held in person\, and are free and open to th e public. LOCATION:Physics/Astronomy Auditorium A102\, 3910 15th Ave NE\, Seattle\, W A\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, United States;X-APPLE-RADIUS=100;X-TITLE=Physics/Astronomy Auditori um A102:geo:0,0 END:VEVENT BEGIN:VEVENT UID:61@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231207T150000 DTEND;TZID=America/Los_Angeles:20231207T160000 DTSTAMP:20231129T195807Z URL:https://escience.washington.edu/events/aws-cloud-security/ SUMMARY:AWS Cloud Security Workshop DESCRIPTION:UW’s Amazon Web Services (AWS) team cordially invites you to attend a monthly workshop hosted at the eScience Institute. These workshop s will consist of a technical component introducing cloud computing concep ts\, discussing best practices\, and an open Q&\;A session to discuss p rojects you are working on or issues you are running into. Following the w orkshop\, we will head off campus for happy hour.\nWorkshop 1: Cloud Secur ity\nThursday\, December 7th\, from 3:00 to 4:00 PM\n\nParticipants can at tend either online over Zoom\, or in person at the WRF Data Science Studio on the 6th floor of the Physics/Astronomy Tower on the UW campus:\nZoom r egistration link\nWRF Data Science Studio campus map LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:64@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240108T090000 DTEND;TZID=America/Los_Angeles:20240111T120000 DTSTAMP:20231212T171605Z URL:https://escience.washington.edu/events/software-carpentry-workshop-3/ SUMMARY:Software Carpentry Workshop DESCRIPTION:Software Carpentry aims to help researchers get their work don e in less time and with less pain by teaching them basic research computin g skills. This hands-on workshop will cover basic concepts and tools\, inc luding program design\, version control\, data management\, and task autom ation. Participants will be encouraged to help one another and to apply wh at they have learned to their own research problems.\nDetails &\; Regis tration\n \;\nWho: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.\nWhere: WRF Data Science Studio\, UW Physics/Astronomy Tower\, 6th Floor\nWhen: Jan 8th through 11th\, 2024\ , from 9:00 a.m. to noon each day\nRequirements: Participants must bring a laptop with a Mac\, Linux\, or Windows operating system (not a tablet\, C hromebook\, etc.) that they have administrative privileges on. LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:63@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240109T170000 DTEND;TZID=America/Los_Angeles:20240201T190000 DTSTAMP:20231211T174320Z URL:https://escience.washington.edu/events/winter-school-2024/ SUMMARY:Winter School: Data Science Tools DESCRIPTION:The eScience Institute offers the annual Winter School to stude nts and lecturers interested in developing basic skills and knowledge of t he tools used in data science. Gaining literacy in topics such as Python\, R\, Jupyter\, and reproducible environments can be beneficial beyond STEM \, including areas like global or public health\, public policy\, social s ciences\, social work\, international relations\, and business management. \n\nThere are no prerequisites to take this course and there is no credit offered. UW faculty\, undergraduate students\, and graduate students are w elcome to apply. This remote workshop will be held over zoom.\nThe deadlin e to apply is January 4th\, 2024\nMore info and registration\nWinter Schoo l 2024 classes will be offered from 5:00 to 7:00 p.m. twice a week on Tues days and Thursdays with identical materials taught on both days. A complet e course is 4 classes - one each week. You do not need to register for all 8 classes.\nClass 1: January 9th or 11th - Python and R\nClass 2: January 16th or 18th - Python and Jupyter\nClass 3: January 23rd or 25th - R and RStudio/Posit\nClass 4: January 30th or February 1st - Reproducible Envi ronments END:VEVENT BEGIN:VEVENT UID:60@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240111T163000 DTEND;TZID=America/Los_Angeles:20240111T172000 DTSTAMP:20231212T212330Z URL:https://escience.washington.edu/events/uwdss-kim/ SUMMARY:UW Data Science Seminar: Jae Yeon Kim DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Thursday\, January 11th from 4:30 to 5:20 p.m. PST. The seminar will feature Jae Yeon Kim\, a senior data scientist at Safety Net Innovations Lab at Code for America\, as well as a research fellow at the SNF Agora Institute and the P3 Lab at Johns Hopkins University.\n\nThe seminar will be held in the El ectrical &\; Computer Engineering Building (ECE)\, Room 105\n\n\n \ ;\n"The Unequal Landscape of Civic Opportunity in America: Evidence from 1 .8 Million Tax Returns"\nAbstract: The hollowing of civil society has thre atened effective implementation of scientific solutions to pressing public challenges—which often depend on cultivating pro-social orientations co mmonly studied under the broad umbrella of social capital. Although robust research has studied the constituent components of social capital from th e demand side (that is\, the orientations people need for collective life in pluralistic societies\, such as trust\, cohesion and connectedness)\, t he same precision has not been brought to the supply side. Here we define the concept of civic opportunity—opportunities people have to encounter civic experiences necessary for developing such orientations—and harness data science to map it across America. We demonstrate that civic opportun ity is more highly correlated with pro-social outcomes such as mutual aid than other measures\, but is unequally distributed\, and its sources are u nderrepresented in the public dialogue. Our findings suggest greater atten tion to this fundamentally uneven landscape of civic opportunity.\n\nBiogr aphy: Jae Yeon Kim (Ph.D. in political science\, UC Berkeley) is a senior data scientist at the Safety Net Innovations Lab at Code for America and a research fellow at the SNF Agora Institute and P3 Lab at Johns Hopkins Un iversity. Kim's research focuses on identity politics\, civic engagement\, and policy implementation in the US\, Canada\, and East Asia.\n\n \;\ nThe UW Data Science Seminar is an annual lecture series at the Universi ty of Washington that hosts scholars working across applied areas of data science\, such as the sciences\, engineering\, humanities and arts along w ith methodological areas in data science\, such as computer science\, appl ied math and statistics. Our presenters come from all domain fields and in clude occasional external speakers from regional partners\, governmental a gencies and industry.\nThe 2023-2024 seminars will be held in person\, and are free and open to the public. LOCATION:Electrical and Computer Engineering Building\, Room 105\, 185 W St evens Way NE\, Seattle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=185 W Stevens Way NE\, Seat tle\, WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=Electrical and Computer Engineering Building\, Room 105:geo:0,0 END:VEVENT BEGIN:VEVENT UID:66@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240116T130000 DTEND;TZID=America/Los_Angeles:20240116T140000 DTSTAMP:20240111T201813Z URL:https://escience.washington.edu/events/aws-office-hours/ SUMMARY:AWS Office Hours DESCRIPTION:UW’s Amazon Web Services (AWS) team is hosting drop-in open o ffice hours at WRF Data Science Studio. Joel Morgan\, Senior Solutions Arc hitect at AWS\, will be available in person for anyone from the UW communi ty to stop by and get help on any cloud-related projects they are working on.\n\nTuesday\, January 16th\, from 1:00 to 2:00 PM\n\nThe WRF Data Scien ce Studio is located on the 6th floor of the Physics/Astronomy Tower on th e UW campus:\nWRF Data Science Studio campus map LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:62@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240118T163000 DTEND;TZID=America/Los_Angeles:20240118T172000 DTSTAMP:20231221T221823Z URL:https://escience.washington.edu/events/uwdss-ebers/ SUMMARY:UW Data Science Seminar: Megan Ebers DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Thursday\, January 18th from 4:30 to 5:20 p.m. PST. The seminar will feature Megan Eb ers\, a postdoctoral scholar in the Steele Lab\, UW Mechanical Engineering .\n\nThe seminar will be held in the Electrical &\; Computer Engineerin g Building (ECE)\, Room 105\n\n\n \;\n"Mobile sensing with shallow rec urrent decoder networks"\nAbstract: Sensing is a fundamental task for the monitoring\, forecasting\, and control of complex systems. In many applica tions\, a limited number of sensors are available and must move with the d ynamics\, such as with wearable technology or ocean monitoring buoys. In t hese dynamic systems\, the sensors’ time history encodes a significant a mount of information that can be extracted for critical tasks. We show tha t by leveraging the time-history of a sparse set of sensors\, we can encod e global information of the measured high-dimensional system using shallow recurrent decoder networks. This paradigm has important applications for technical challenges in climate modeling\, natural disaster evaluation\, a nd personalized health monitoring\; we focus especially on how this paradi gm has the potential to transform the way we monitor and manage movement-r elated health outcomes.\n\nBio: Megan Ebers is a postdoctoral scholar in a pplied mathematics with UW's NSF AI Institute in Dynamic Systems. In her P hD research\, she developed and applied machine learning methods for dynam ics systems to understand and enable human mobility. Her postdoctoral rese arch focuses on data-driven and reduced-order methods for complex systems\ , so as to continue her work in human-centered research challenges\, as we ll as to extend her research to a broader set of technical challenges\, in cluding turbulent flow modeling\, natural disaster monitoring\, and acoust ic object detection.\nThe UW Data Science Seminar is an annual lecture s eries at the University of Washington that hosts scholars working across a pplied areas of data science\, such as the sciences\, engineering\, humani ties and arts along with methodological areas in data science\, such as co mputer science\, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional part ners\, governmental agencies and industry.\nThe 2023-2024 seminars will be held in person\, and are free and open to the public. LOCATION:Electrical and Computer Engineering Building\, Room 105\, 185 W St evens Way NE\, Seattle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=185 W Stevens Way NE\, Seat tle\, WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=Electrical and Computer Engineering Building\, Room 105:geo:0,0 END:VEVENT BEGIN:VEVENT UID:68@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240124T140000 DTEND;TZID=America/Los_Angeles:20240124T150000 DTSTAMP:20240116T235927Z URL:https://escience.washington.edu/events/dssg24-student-info-session/ SUMMARY:DSSG 2024 Info Session: Student Fellows DESCRIPTION:eScience and Open Scholarship Commons are hosting an informatio nal session for students interested in applying to become DSSG 2024 Studen t Fellows. This hybrid event will be held online over zoom\, as well as in person in the Suzzallo Library on the UW campus.\nZoom event info\nIn per son event info\nThe University of Washington Data Science for Social Good  (DSSG) summer program brings together students\, stakeholders\, and data and domain researchers to work on focused\, collaborative projects for so cietal benefit. To tackle complex societal challenges\, UW DSSG teams take a multi-dimensional approach that integrates data science techniques\, et hical thinking\, and stakeholder engagement to generate real-world benefit s. Student fellows work on interdisciplinary teams led by project leads fr om academia\, nonprofits\, and government\, along with data scientists at the eScience Institute who offer technical expertise and guidance. Through out the 10-week summer program\, students also participate in tutorials\, workshops\, mentoring\, and career development talks with panelists who wo rk in a variety of sectors. This hands-on program emphasizes learning oppo rtunities for all participants as they collaboratively navigate exciting a nd challenging teamwork in pursuit of Data Science for Social Good.\nLearn more about DSSG\n \;\n\n END:VEVENT BEGIN:VEVENT UID:69@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240125T140000 DTEND;TZID=America/Los_Angeles:20240125T150000 DTSTAMP:20240117T000535Z URL:https://escience.washington.edu/events/dssg24-project-info-session/ SUMMARY:DSSG 2024 Info Session: Project Leads DESCRIPTION:eScience and Open Scholarship Commons are hosting an informatio nal session for researchers interested in becoming a Project Lead for our DSSG 2024 program. This event will be held online over zoom.\nRegister for the zoom event\nThe University of Washington Data Science for Social Goo d (DSSG) summer program brings together students\, stakeholders\, and data and domain researchers to work on focused\, collaborative projects for so cietal benefit. Each year\, the eScience Institute selects several project s and provide support by assigning four Student Fellows selected and paid by the eScience Institute to work on the project full-time\, along with a Data Scientist from the eScience Institute who serves as a technical advis or and helps to co-manage the project. We look for projects that would ben efit from collaboration on data science approaches\, such as scalable data management\, statistical analysis\, machine learning\, open-source softwa re development\, cloud and cluster computing\, and data visualization.\nLe arn more about DSSG\n \;\n\n END:VEVENT BEGIN:VEVENT UID:67@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240125T163000 DTEND;TZID=America/Los_Angeles:20240125T172000 DTSTAMP:20240117T174749Z URL:https://escience.washington.edu/events/uwdss-gorjifard/ SUMMARY:UW Data Science Seminar: Sayeh Gorjifard DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Thursday\, January 25th from 4:30 to 5:20 p.m. PST. The seminar will feature Sayeh Go rjifard\, a postdoctoral scholar with UW Genome Sciences.\n\nThe seminar w ill be held in the Electrical &\; Computer Engineering Building (ECE)\, Room 105\n\n\n \;\n"Decoding Terminators: Synthetic terminator design s enabled by a comprehensive analysis of plant terminators"\nAbstract: The 3’ end of a gene\, often called a terminator\, modulates mRNA stability \, localization\, translation\, and polyadenylation. Here\, we adapted Pla nt STARR-seq\, a massively parallel reporter assay\, to measure the activi ty of over 50\,000 terminators from the plants Arabidopsis thaliana and  Zea mays. We characterize thousands of plant terminators\, including man y that outperform bacterial terminators commonly used in plants. Terminato r activity is species-specific\, differing in tobacco leaf and maize proto plast assays. While recapitulating known biology\, our results reveal the relative contributions of polyadenylation motifs to terminator strength. W e built a robust computational model to predict terminator strength and us ed it to conduct in silico evolution that generated optimized synthetic terminators. Additionally\, we discover alternative polyadenylation sites across tens of thousands of terminators\; however\, the strongest terminat ors tend to have a dominant cleavage site. Our results establish features of plant terminator function and identify strong naturally occurring and s ynthetic terminators.\nBio: Sayeh Gorjifard joined the Genome Sciences Dep artment at the University of Washington as a graduate student in 2018. She graduated in the fall of 2023 and has since continued as a one-year postd octoral scholar to conclude ongoing research. Sayeh received her undergrad uate degrees in Chemistry and Art from Dartmouth College in New Hampshire\ , where she focused on manganese-catalyzed reactions to 2-cyanoindoles. Fo llowing her undergraduate studies\, she researched as a CRTA fellow at the National Cancer Institute\, studying the effect of the gut microbiome on the response to cancer therapy. Subsequently\, she earned her Master's deg ree in Biotechnology from Johns Hopkins University as a Molecular Target a nd Drug Discovery Fellow. During her master's program\, she played a role in developing a pharmacogenomic pipeline to predict the most effective dru g combinations for Multiple Myeloma patients. Sayeh's journey continued a t the UW Genome Sciences for her Ph.D.\, where she studied CRISPR technolo gy development and plant regulatory grammar.\nThe UW Data Science Seminar  is an annual lecture series at the University of Washington that hosts s cholars working across applied areas of data science\, such as the science s\, engineering\, humanities and arts along with methodological areas in d ata science\, such as computer science\, applied math and statistics. Our presenters come from all domain fields and include occasional external spe akers from regional partners\, governmental agencies and industry.\nThe 20 23-2024 seminars will be held in person\, and are free and open to the pub lic. LOCATION:Electrical and Computer Engineering Building\, Room 105\, 185 W St evens Way NE\, Seattle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=185 W Stevens Way NE\, Seat tle\, WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=Electrical and Computer Engineering Building\, Room 105:geo:0,0 END:VEVENT BEGIN:VEVENT UID:71@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240201T150000 DTEND;TZID=America/Los_Angeles:20240201T160000 DTSTAMP:20240125T165747Z URL:https://escience.washington.edu/events/aws-cloud-seminar/ SUMMARY:AWS Cloud Seminar DESCRIPTION:UW’s Amazon Web Services (AWS) team is hosting a seminar with Senior Solutions Architect Joel Morgan\, who will walk us through the new services and technologies coming to the AWS cloud in 2024. We'll review h ow to make use of these new services to further your research and IT infra structure\, and be available for any questions or consultation needs you m ight have.\n\nTuesday\, February 1st\, from 3:00 to 4:00 PM\, with happy h our to follow.\n\nThe WRF Data Science Studio is located on the 6th floor of the Physics/Astronomy Tower on the UW campus:\nWRF Data Science Studio campus map\n LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:70@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240201T163000 DTEND;TZID=America/Los_Angeles:20240201T172000 DTSTAMP:20240123T231102Z URL:https://escience.washington.edu/events/uwdss-komp/ SUMMARY:UW Data Science Seminar: Evan Komp DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Thursday\, February 1st from 4:30 to 5:20 p.m. PST. The seminar will feature Evan Kom p\, recent PhD in Chemical Engineering Data Science.\n\nThe seminar will b e held in the Electrical &\; Computer Engineering Building (ECE)\, Room 105\n\n\n \;\n"Leveraging Nature's Translation Between Low and High T emperature Proteins with Deep Learning"\nAbstract: This work presents Neur al Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT)\, a novel approach for designing and ranking high-temperature sta ble proteins using neural machine translation. The training required the d evelopment of a new dataset of protein homologous pairs occurring in organ isms adapted to low and high temperatures\, which is detailed. The dataset is orders of magnitude larger than any dataset of its kind\, with 25 mill ion protein pairs. By training on over 4 million of the highest quality pa irs\, the model demonstrates promising capability in targeting thermal sta bility. A designed variant of the Drosophila melanogaster Engrailed Home odomain shows increased stability at high temperatures\, as validated by e stimators and molecular dynamics simulations. Furthermore\, NOMELT achieve s zero-shot predictive capabilities in ranking experimental melting and ha lf-activation temperatures across two protein families. It achieves this w ithout requiring extensive homology data or massive training datasets as d o existing zero-shot predictors by specifically learning thermophilicity\, as opposed to all natural variation. These findings underscore the potent ial of leveraging organismal growth temperatures in data-rich\, context-de pendent design of proteins for enhanced thermal stability.\nBio: Evan Komp recently finished his PhD in Chemical Engineering Data Science at the Uni versity of Washington under the amazing Prof. David Beck\, meanwhile award ed the data science fellowship from the Clean Energy Institute and a stint as a machine learning engineer in pharma. He has worked on a number of to pics at the intersection of deep learning and the chemical sciences\, incl uding molecular properties\, chemical reaction rates\, and protein thermal stability. Evan is a strong advocate for the use of data science to help us develop a more sustainable\, climate resilient and friendly society\, a nd as such encourages everyone who works in a compute intensive environmen t to track their computation's carbon emissions.\nThe UW Data Science Semi nar is an annual lecture series at the University of Washington that host s scholars working across applied areas of data science\, such as the scie nces\, engineering\, humanities and arts along with methodological areas i n data science\, such as computer science\, applied math and statistics. O ur presenters come from all domain fields and include occasional external speakers from regional partners\, governmental agencies and industry.\nThe 2023-2024 seminars will be held in person\, and are free and open to the public. LOCATION:Electrical and Computer Engineering Building\, Room 105\, 185 W St evens Way NE\, Seattle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=185 W Stevens Way NE\, Seat tle\, WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=Electrical and Computer Engineering Building\, Room 105:geo:0,0 END:VEVENT BEGIN:VEVENT UID:65@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240208T163000 DTEND;TZID=America/Los_Angeles:20240208T172000 DTSTAMP:20240111T175831Z URL:https://escience.washington.edu/events/uwdss-dorkenwald/ SUMMARY:UW Data Science Seminar: Sven Dorkenwald DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Thursday\, February 8th from 4:30 to 5:20 p.m. PST. The seminar will feature Sven Dor kenwald\, a Shanahan Foundation Fellow with the Allen Institute and the Un iversity of Washington.\n\nThe seminar will be held in the Electrical & \; Computer Engineering Building (ECE)\, Room 105\n\n\n \;\n"Reconstru cting the synaptic wiring diagram of the fruit fly brain"\nAbstract: Conne ctions between neurons can be mapped by acquiring and analyzing electron m icroscopic (EM) brain images. In recent years\, this approach has been app lied to chunks of brains to reconstruct local connectivity maps that are h ighly informative\, yet inadequate for understanding brain function more g lobally. We reconstructed the first neuronal wiring diagram of a whole adu lt brain\, containing 5×107 chemical synapses between ~139\,000 neurons r econstructed from a female Drosophila melanogaster. The resource also inco rporates annotations of cell classes and types\, nerves\, hemilineages\, a nd predictions of neurotransmitter identities. In this talk\, I will discu ss the technological progress in machine learning and computer systems tha t lead up to the creation of this resource. Further\, I will demonstrate i ts impact by highlighting how the connectome can be used to study the glob al organization of the brain and facilitates the tracing synaptic pathways from the inputs (e.g.\, sensory neurons) to outputs (e.g. descending neur ons). \n\nBio: Sven Dorkenwald joined the Allen Institute and the Universi ty of Washington as a Shanahan Fellow in September 2023. He received his u ndergraduate degree in Physics and a Masters degree in Computer Engineerin g at the University of Heidelberg in Germany. While in Heidelberg\, he wor ked on automated image analysis in connectomics with Jörgen Kornfeld in t he department of Winfried Denk at the Max Planck Institute for Medical Res earch. Sven received his Ph.D. in Computer Science and Neuroscience from P rinceton University\, where he worked with Sebastian Seung and Mala Murthy . During his PhD\, he developed approaches for the reconstruction and anal ysis of neuronal circuits from Electron Microscopy images and spearheaded the FlyWire consortium effort that produced a synapse-resolution connectom e of an adult Drosophila brain. Concurrently\, Sven devised a self-supervi sed approach for efficient annotation of cell reconstructions as a student researcher at Google Research. As a Shanahan Fellow\, Sven is pursuing th e integration neuroscience datasets from multiple modalities.\nThe UW Dat a Science Seminar is an annual lecture series at the University of Washin gton that hosts scholars working across applied areas of data science\, su ch as the sciences\, engineering\, humanities and arts along with methodol ogical areas in data science\, such as computer science\, applied math and statistics. Our presenters come from all domain fields and include occasi onal external speakers from regional partners\, governmental agencies and industry.\nThe 2023-2024 seminars will be held in person\, and are free an d open to the public. LOCATION:Electrical and Computer Engineering Building\, Room 105\, 185 W St evens Way NE\, Seattle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=185 W Stevens Way NE\, Seat tle\, WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=Electrical and Computer Engineering Building\, Room 105:geo:0,0 END:VEVENT BEGIN:VEVENT UID:72@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240215T163000 DTEND;TZID=America/Los_Angeles:20240215T172000 DTSTAMP:20240212T173358Z URL:https://escience.washington.edu/events/uwdss-mccormick/ SUMMARY:UW Data Science Seminar: Tyler McCormick DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Thursday\, February 15th from 4:30 to 5:20 p.m. PST. The seminar will feature Tyler M cCormick\, a Senior Data Science Fellow and a Professor of Statistics and Sociology at UW.\n\nThe seminar will be held in the Electrical &\; Comp uter Engineering Building (ECE)\, Room 105\n\n\n \;\n"Robustly estimat ing heterogeneity in factorial data using Rashomon Partitions"\nAbstract: Many statistical analyses begin with a fundamental question: How does the outcome vary with observable covariates?  Do more experienced employees r eceive higher wages? Do vaccinated individuals get sick less frequently th an those who are unvaccinated? Do trout in warm water eat less than trout in cold water? Does Venus's atmosphere contain a higher fraction of nitrog en than Mars?  Do patients taking Metformin have lower A1C measures than those taking DPP4-inhibitors?\n\nIn settings where these covariates are di screte\, this problem yields a factorial-like structure\, and it is imposs ible to enumerate all possible combinations of covariates for any scientif ically interesting setting. In this paper\, we propose an approach to enum erating heterogeneity in the relationship between an outcome and discrete covariates by creating a Rashomon Partitions Set (RPS). Each Rashomon part ition consists of the feature combinations that maximize heterogeneity in the outcome space. We construct this by pooling similar feature combinati ons using priors over pooling patterns in an overarching Bayesian model.  We show that we can characterize the set of Rashomon Partitions in terms of its fraction of the overall posterior and size.  Further\, we demonstr ate that the RPS is enumerable in meaningful settings by leveraging the in sight that many potential combinations of features are\, in practice\, non sensical for pooling because they represent different dimensions in the co variate space.  We demonstrate RPS construction in the context of two pra ctical settings: finding heterogeneity in outcomes of a randomized trial a nd examining racial disparities in health outcomes in a large clinical dat aset.  This is joint work with Arun Chandrasekhar (Stanford Economics) an d Aparajithan Venkateswaran (UW Statistics).\n\n\nBio: Tyler McCormick is a Professor of Statistics and Sociology at the University of Washington\, where he is also a core faculty member in the Center for Statistics and th e Social Sciences.  He is also a Senior Data Science Fellow at the eScien ce Institute.  Tyler's work develops statistical models that infer depend ence structure in scientific settings where data are sparsely observed or observed subject to error.  His recent projects include estimating featur es of social networks (e.g. the degree of clustering or how central an ind ividual is) using data from standard surveys\, inferring a likely cause of death (when deaths happen outside of hospitals) using reports from surviv ing caretakers\, and quantifying &\; communicating uncertainty in predi ctive models for global health policymakers.  He holds a Ph.D. in Statist ics (with distinction) from Columbia University and is the recipient of an NIH New Innovator (DP2) Award\, NIH Career Development (K01) Award\, Army Research Office Young Investigator Program Award\, and a Google Faculty R esearch Award.  Tyler is the former Editor of the Journal of Computation al and Graphical Statistics (JCGS) and a Fellow of the American Statistic al Association.\nThe UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science\, such as the sciences\, engineering\, humanities a nd arts along with methodological areas in data science\, such as computer science\, applied math and statistics. Our presenters come from all domai n fields and include occasional external speakers from regional partners\, governmental agencies and industry.\nThe 2023-2024 seminars will be held in person\, and are free and open to the public. LOCATION:Electrical and Computer Engineering Building\, Room 105\, 185 W St evens Way NE\, Seattle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=185 W Stevens Way NE\, Seat tle\, WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=Electrical and Computer Engineering Building\, Room 105:geo:0,0 END:VEVENT BEGIN:VEVENT UID:73@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240222T163000 DTEND;TZID=America/Los_Angeles:20240222T172000 DTSTAMP:20240212T195239Z URL:https://escience.washington.edu/events/uwdss-magallanes/ SUMMARY:UW Data Science Seminar: Jose Manuel Magallanes DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Thursday\, February 22nd from 4:30 to 5:20 p.m. PST. The seminar will feature Jose Ma nuel Magallanes\, a Senior Data Science Fellow and Professor of Social Sci ences at Pontificia Catolica del Peru\, where he is also the director of t he Institute for Social Analytics and Strategic Intelligence (PULSO PUCP). \n\nThe seminar will be held in the Electrical &\; Computer Engineering Building (ECE)\, Room 105\n\n\n \;\n"A gentle and comparative introdu ction to social network analysis using Python and R"\nAbstract: This prese ntation will introduce how you can use Python and R to start your analysis of social networks. Both R and Python can deal effectively with the const ruction\, organization\, description\, pattern recognition\, plotting\, mo deling and analysis of networks\, so this workshop will show you the basic steps to do that.\nBio: Jose Manuel Magallanes is currently a full at the Department of Social Sciences Professor at Pontificia Catolica del Peru\, where he is also the director of the Institute for Social Analytics and S trategic Intelligence (PULSO PUCP). He is also a part time professor at Un iversidad Nacional Mayor de San Marcos\, and a Lecturer at the Data Analyt ics and Computational Social Science program  at University of Massachuse tts - Amherst. He is also the director of the UW eScience Winter School of Data Science Tools.\n\nHe has been eScience Senior Data Scientist\, and  a Visiting Professor of Computational Public Policy at the Evans School o f Public Policy and Governance since Mid 2015.  Jose Manuel appointment i s funded by the University of Washington’s eScience Institute thanks to the Washington Research Fund\,  the Alfred P. Sloan Foundation\, and the Gordon and Betty Moore Foundation\, where he is  a Senior Data Science Fe llow.Professor Magallanes has two Doctoral degrees. One in Computational S ocial Science from George Mason University\, and another one in Psychology from Universidad Nacional Mayor de San Marcos. He also holds a Master deg ree in Political Science and Public Management  from Pontificia Universid ad Católica del Perú. He has received multidisciplinary training on comp utational approaches on governance matters from University Michigan (ICPSR )\, National University of Australia\, National University of Singapore (I SS)\, University of Chicago (Argonne NL)\, Carnegie Mellon University (CAS OS)\, and Harvard Kennedy School.\n\n\nThe UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science\, such as the sciences\, engi neering\, humanities and arts along with methodological areas in data scie nce\, such as computer science\, applied math and statistics. Our presente rs come from all domain fields and include occasional external speakers fr om regional partners\, governmental agencies and industry.\nThe 2023-2024 seminars will be held in person\, and are free and open to the public. LOCATION:Electrical and Computer Engineering Building\, Room 105\, 185 W St evens Way NE\, Seattle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=185 W Stevens Way NE\, Seat tle\, WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=Electrical and Computer Engineering Building\, Room 105:geo:0,0 END:VEVENT BEGIN:VEVENT UID:76@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240229T150000 DTEND;TZID=America/Los_Angeles:20240229T170000 DTSTAMP:20240220T194125Z URL:https://escience.washington.edu/events/seattle-research-software-engin eer-meetup/ SUMMARY:Seattle Research Software Engineer Meetup DESCRIPTION:Join us for the Seattle Research Software Engineer (RSE) Meetup \, a FREE event hosted and sponsored by the Scientific Software Engineeri ng Center (SSEC) @ eScience Institute at the University of Washington. Thi s networking event is a great opportunity for Research Software Engineers\ , developers\, and scientists in the Seattle area to connect\, network\, a nd build a community of RSEs.\nRegister for Free Here\nWhether you're an e xperienced RSE or just starting out in the field\, this meetup is designed to provide a friendly and inclusive environment where you can meet like-m inded professionals\, share your experiences\, and expand your professiona l network. Our goal is to foster a supportive community of RSEs in the reg ion and create opportunities for collaboration and knowledge exchange.\n\n The event will feature networking activities\, icebreakers\, and interacti ve discussions to help you get to know your fellow RSEs and build meaningf ul connections. You'll have the opportunity to exchange ideas\, learn from each other's experiences\, and explore potential collaborations in a rela xed and informal setting.\n\nThis is just the beginning! Our future events will feature lightning talks\, demos\, and interactive discussions on a w ide variety of topics related to research software development\, including best practices\, tools\, techniques\, and challenges faced by RSEs in var ious domains. We'll cover topics ranging from programming languages\, vers ion control\, data management\, software testing\, and more. You'll have t he opportunity to hear from experienced RSEs and researchers\, learn about cutting-edge projects\, and engage in lively discussions that will help y ou broaden your knowledge and stay up-to-date with the latest developments in the field.\n\nDon't miss this chance to connect with fellow RSEs\, est ablish new relationships\, and be part of a growing community of Research Software Engineers in the Seattle area. Food and refreshments will be prov ided\, and there will be ample time for networking and socializing. Come j oin us for an evening of building professional connections\, sharing insig hts\, and fostering collaborations!\n\nWe look forward to welcoming you to the Seattle RSE Meetup and starting this exciting journey of building a s trong RSE community in the region! Register now to secure your spot.\nThe event will be held in the WRF Data Science Studio on the UW campus\n\n[cap tion id="attachment_17031" align="aligncenter" width="683"] UW Physics/Ast ronomy Tower (PAT): 3910 15th Avenue NE\, 6th floor - click for interactiv e map[/caption]\n\n \; ATTACH;FMTTYPE=image/jpeg:https://escience.washington.edu/wp-content/uploa ds/2023/04/SSEC-white-sq.jpg LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:74@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240229T163000 DTEND;TZID=America/Los_Angeles:20240229T172000 DTSTAMP:20240207T172224Z URL:https://escience.washington.edu/events/uwdss-ferraioli-2/ SUMMARY:UW Data Science Seminar: Julia Ferraioli DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Thursday\, February 29th from 4:30 to 5:20 p.m. PST. The seminar will feature Julia F erraioli\, an AI/ML Open Source Strategist with Amazon Web Services (AWS). \n\nThe seminar will be held in the Electrical &\; Computer Engineering Building (ECE)\, Room 105\n\n\n \;\n"Data-driven open source projects : preventing random acts of metrics"\nAbstract: People often approach gain ing adoption of their open source projects as more of an art than science. When maintainers attempt to use a data-driven approach\, they find the in sights yielded by their analyses insufficient to make informed decisions. We will look at common missteps in using data in open source and examine h ow we can use and contextualize data appropriately to bring in and sustain contributors.\nBio: Julia Ferraioli is an open source engineer\, scientis t\, and analyst with a decade of experience in launching\, managing\, and optimizing open source projects at scale. She currently works at AWS as th e AI/ML Open Source Strategist\, providing guidance and expertise in the o pen source machine learning field. Additionally\, Julia is a co-founder of Open Source Stories\, contributor to LeadDev\, and open source sustainabi lity researcher. Her background includes research in machine learning\, ro botics\, HCI\, and accessibility. Julia finds energy in developing creativ e demos\, creating beautiful documents\, and rainbow sprinkles. She’s al so a fierce supporter of LaTeX\, the Oxford comma\, and small pull request s.\n\n\n\nThe UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science\, such as the sciences\, engineering\, humanities and arts along with methodological areas in data science\, such as computer scienc e\, applied math and statistics. Our presenters come from all domain field s and include occasional external speakers from regional partners\, govern mental agencies and industry.\nThe 2023-2024 seminars will be held in pers on\, and are free and open to the public. LOCATION:Electrical and Computer Engineering Building\, Room 105\, 185 W St evens Way NE\, Seattle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=185 W Stevens Way NE\, Seat tle\, WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=Electrical and Computer Engineering Building\, Room 105:geo:0,0 END:VEVENT BEGIN:VEVENT UID:81@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240307T150000 DTEND;TZID=America/Los_Angeles:20240307T160000 DTSTAMP:20240305T220821Z URL:https://escience.washington.edu/events/aws-march24/ SUMMARY:AWS Cloud Workshop DESCRIPTION:UW’s Amazon Web Services (AWS) team is hosting another worksh op with Senior Solutions Architect Joel Morgan\, who will provide an overv iew of the Research and Engineering Studio (RES) on AWS. RES was released in January and it provides an easy-to-use web-based portal for administrat ors to create and manage secure cloud-based research and engineering envir onments. With just a few clicks\, scientists and engineers can create and connect to Windows and Linux virtual desktops that come with pre-installed applications\, shared data\, and collaboration tools they need. With RES\ , administrators can define permissions\, set budgets\, and monitor resour ce utilization through a single web interface.\n\nThursday\, March 7th\, f rom 3:00 to 4:00 PM\, with happy hour to follow.\nZoom registration link\n The WRF Data Science Studio is located on the 6th floor of the Physics/Ast ronomy Tower on the UW campus:\nWRF Data Science Studio campus map\n LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:75@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240307T163000 DTEND;TZID=America/Los_Angeles:20240307T172000 DTSTAMP:20240304T183749Z URL:https://escience.washington.edu/events/uwdss-sanger/ SUMMARY:UW Data Science Seminar: Morgan Sanger DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Thursday\, March 7th from 4:30 to 5:20 p.m. PST. The seminar will feature Morgan Sang er\, a PhD scholar in geotechnical engineering at the University of Washin gton.\n\nThe seminar will be held in the Electrical &\; Computer Engine ering Building (ECE)\, Room 105\n\n\n \;\n"Mechanics-informed\, geospa tial machine learning for natural hazard planning and response"\nAbstract: Hazard-resilient communities and infrastructure networks rely on hazard p redictions that can be made accurately\, quickly\, at regional scale\, and at high resolution. In earthquake-prone regions\, earthquake-induced soil liquefaction is one of the most relevant and consequential geotechnical h azards. Accurate soil liquefaction hazard analyses require geotechnical te sting\, which cannot be continuously performed across large areas\, thus p resenting the need for “geospatial” liquefaction models. This project employs supervised machine learning to extend engineering mechanics and sp arse geotechnical testing to map-scale using publicly available geospatial variables. In doing so\, this model can be used in network analysis for e mergency response planning\, evaluating community impacts\, and identifyin g mitigation priorities.\nBio: Morgan Sanger\, P.E.\, is a PhD student sch olar in geotechnical engineering at the University of Washington. Her doct oral research involves applying machine learning to large geospatial and g eotechnical data sets for improved natural hazard modeling and risk manage ment. Morgan is a 2023-2024 Herbold Data Science Fellow for the College of Engineering.\n\n\n\nThe UW Data Science Seminar is an annual lecture ser ies at the University of Washington that hosts scholars working across app lied areas of data science\, such as the sciences\, engineering\, humaniti es and arts along with methodological areas in data science\, such as comp uter science\, applied math and statistics. Our presenters come from all d omain fields and include occasional external speakers from regional partne rs\, governmental agencies and industry.\nThe 2023-2024 seminars will be h eld in person\, and are free and open to the public. LOCATION:Electrical and Computer Engineering Building\, Room 105\, 185 W St evens Way NE\, Seattle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=185 W Stevens Way NE\, Seat tle\, WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=Electrical and Computer Engineering Building\, Room 105:geo:0,0 END:VEVENT BEGIN:VEVENT UID:80@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240325T133000 DTEND;TZID=America/Los_Angeles:20240325T143000 DTSTAMP:20240313T161351Z URL:https://escience.washington.edu/events/seminar-spector/ SUMMARY:Applying Data Science and AI Effectively DESCRIPTION:\n\nPlease join us for a special guest seminar on Monday\, Marc h 25th from 1:30 to 2:30 p.m. in the WRF Data Science Studio. The seminar will feature Dr. Alfred Spector\, a Visiting Scholar at MIT and a Senior A dvisor at Blackstone. The seminar will be offered in-person in the WRF Dat a Science Studio Seminar Room\, 6th floor of the UW Physics/Astronomy Towe r - campus map\n\n\n"Applying Data Science and AI Effectively"\nAbstract: Applying data science and artificial intelligence effectively requires a c onsiderably broader focus than just data and machine learning. Based on th e speaker and his co-authors' recent book (Data Science in Context\, Cambr idge Univ. Press\, 2022)\, this presentation distills these additional cha llenges into a rubric and illustrates its application with a multitude of examples from diverse domains. Beyond the rubric\, the presentation also p resents useful frameworks to help in making the complex trade-offs that ar e often inherent in AI and DS solutions. While the talk should have practi cal value to those applying AI and DS techniques\, it also illustrates con temporary research challenges.\nBio: Dr. Alfred Spector is a Visiting Scho lar at MIT and a Senior Advisor at Blackstone. His career has led him from innovation in large-scale\, networked computing systems to broad engineer ing and research leadership. Recently\, he co-authored a textbook\, “Dat a Science in Context: Foundations\, Challenges\, Opportunities.”\nPrevio usly\, Spector was CTO and Head of Engineering at Two Sigma Investments. B efore that\, he spent eight years as VP of Research and Special Initiative s at Google\, and he held various senior-level positions at IBM\, includin g as global VP of Services and Software Research and global CTO of IBM’s Software Business. Earlier in his career\, he founded Transarc Corporatio n\, a pioneer in distributed transaction processing and wide-area file sys tems\, and he was a tenured professor at Carnegie Mellon University.\n\nSp ector is a Hertz Fellow and also a Fellow of both the ACM and the IEEE. He is a member of the National Academy of Engineering and the American Acade my of Arts and Sciences. Dr. Spector won the 2001 IEEE Kanai Award for Dis tributed Computing and the 2016 ACM Software Systems Award. In 2018-19\, D r. Spector lectured widely as a Phi Beta Kappa Scholar (for example\, on t he growing importance of computer science across all disciplines based on the evocative phrase\, “CS+X”). He has been a member of the ACM Turing Award Committee and has done national service through chairing the NSF’ s CISE Advisory Board and membership on the Army and now the Defense Scien ce Boards. He has had extensive international experience due to broad resp onsibilities at IBM\, Google\, and Two Sigma. Dr. Spector obtained a Ph.D. in computer science from Stanford and a B.A. in applied math from Harvard . LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:77@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240327T163000 DTEND;TZID=America/Los_Angeles:20240327T172000 DTSTAMP:20240312T221458Z URL:https://escience.washington.edu/events/uwdss-incubator-1/ SUMMARY:UW Data Science Seminar: Winter Incubator DESCRIPTION:Please join us for a UW Data Science Seminar on Wednesday\, Mar ch 27th from 4:30 to 5:20 p.m. PST. The seminar will feature two projects from Diane Xue and George Brencher\, who participated in our 2024 Data Sci ence Incubator program at the eScience Institute.\n2024 Spring Quarter sem inars will be held in PAA A118 - campus map\n \;\n"Polygenic and Conte xtual Determinants of Alzheimer's Disease and Related Dementias"\nAbstract : The goal of this project is to model multi-level macro- and meso- enviro nmental factors including ambient pollutants\, socioeconomic status\, dens ity of physical activity facilities and social engagement destinations. al ongside polygenic scores that summarize individual-level genetic risk for AD in order to determine what social and environmental factors remain sign ificantly associated with dementia risk and/or cognitive decline after con trolling for PRS.  Additionally\, we want to investigate whether effects of social and environmental factors differ for high- and low- genetic risk groups. Social\, built\, and physical environmental variables that are as sociated with healthy controls who are at high genetic risk can be further investigated as population-level solutions for promoting AD resilience. F urthermore\, early prediction of AD is key to prevention. The results of t he proposal will prepare us to integrate genetic and non-genetic factors f or risk prediction\, moving us close to precision treatments.\n\n\n"Charac terizing glacial lake outburst flood hazard at a regional scale using fuse d InSAR-speckle tracking surface displacement time series"\nAbstract: Usin g satellite synthetic aperture radar remote sensing\, we have developed a workflow allowing us to quantify surface changes that can contribute to gl acial lake outburst flood (GLOF) likelihood\, including landslide movement and moraine dam subsidence. Our approach fuses interferometric synthetic aperture radar (InSAR) and SAR speckle tracking data to accurately capture deformation as fast as hundreds of meters per year and as slow as <\;1 cm per year. During this incubator project\, we developed infrastructure t o deploy our workflow on the cloud using Github Actions\, allowing us to q uickly and efficiently process large radar datasets and create surface dis placement time series. We applied this processing pipeline to measure surf ace displacement from 2017-present day with high spatial and temporal reso lution for the areas surrounding selected hazardous glacial lakes in Nepal \, India\, and China. The resulting multi-year displacement time series al low us to detect and track intra- and inter-annual changes of dynamic land slide\, permafrost\, and glacial features and precisely quantify rates of moraine dam subsidence\, significantly improving our understanding of GLOF hazard and providing a critical missing input to existing risk analysis f rameworks. We use radar data acquired in two orientations to decompose sur face displacement into vertical and horizontal components\, allowing us to understand the contribution of ice melt\, ice flow\, and other processes to ground movement and to quantify how those processes change on seasonal and yearly time scales. These results have implications not only for GLOF hazard\, but also alpine geomorphology and glaciology\, as we learn about processes associated with thinning and retreat of debris-covered glaciers. \n\n\n\n\nThe UW Data Science Seminar is an annual lecture series at the U niversity of Washington that hosts scholars working across applied areas o f data science\, such as the sciences\, engineering\, humanities and arts along with methodological areas in data science\, such as computer science \, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners\, governm ental agencies and industry.\n\n \;\n\nThe 2023-2024 seminars will be held in person\, and are free and open to the public.\n\n\n\n LOCATION:Physics/Astronomy Auditorium\, room A118\, Seattle\, WA\, X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Seattle\, WA\, ;X-APPLE-RAD IUS=100;X-TITLE=Physics/Astronomy Auditorium\, room A118:geo:0,0 END:VEVENT BEGIN:VEVENT UID:78@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240403T163000 DTEND;TZID=America/Los_Angeles:20240403T172000 DTSTAMP:20240312T215028Z URL:https://escience.washington.edu/events/uwdss-incubator-2/ SUMMARY:UW Data Science Seminar: Winter Incubator DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Wednesday\, April 3rd from 4:30 to 5:20 p.m. PST. The seminar will feature two projec ts from Nino Migineishvili and Tabitha Harrison\, who participated in our 2024 Data Science Incubator program at the eScience Institute.\n\n2024 Spr ing Quarter seminars will be held in PAA A118 - campus map\n\n\n \;\n" Assessing Influences of Wildfires on Park Visitation Patterns Using Gravit y"\nAbstract: Wildfires have been growing in size\, duration\, and destruc tivity\, resulting in more decisive calls to improve forest health and pro tect communities. Wildfire fuel treatments – which  involve reducing or removing vegetation from fire-prone areas – are one strategy for reduci ng wildfire risk. Where to conduct fuel treatments implementation is prima rily based on biophysical risk factors. Yet wildfires also disrupt recreat ional utilization of public lands\, which in turn affects societal well-be ing and the numerous physical and mental health benefits of recreating in nature. Given this\, the aim of this project is to develop approaches for estimating recreation on public lands and quantify how recreationalists re spond to wildfires and wildfire treatments on the landscape. The approach uses gravity models with trips to public lands sourced from AllTrails.\n\n \n"Investigating germline genetic influence on somatic immune traits in no n-cancerous tissues"\nAbstract: Cancer is a significant health burden in t he US\, causing substantial morbidity and mortality. This research project builds on past studies demonstrating that inherited genetic variants can influence how our immune system affects cancer risk and survival. While pr ior work has linked aspects of the immune system to tumors\, this project focuses on understanding how our inherited genetic makeup affects immune f unction in healthy tissues. Using publicly available data from dbGaP and G TEx\, we will examine how inherited immune-related genetic markers (in the HLA region) relate to immune function in non-cancerous tissues in the lun g\, breast\, prostate\, and colon. We will then investigate if genetic mar ker variations that affect immune traits in healthy tissues are associated with developing common solid cancers.\n\n\n\n\n\nThe UW Data Science Semi nar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science\, such as the scien ces\, engineering\, humanities and arts along with methodological areas in data science\, such as computer science\, applied math and statistics. Ou r presenters come from all domain fields and include occasional external s peakers from regional partners\, governmental agencies and industry.\n\n&n bsp\;\n\nThe 2023-2024 seminars will be held in person\, and are free and open to the public.\n\n LOCATION:Physics/Astronomy Auditorium\, room A118\, Seattle\, WA\, X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Seattle\, WA\, ;X-APPLE-RAD IUS=100;X-TITLE=Physics/Astronomy Auditorium\, room A118:geo:0,0 END:VEVENT BEGIN:VEVENT UID:79@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240410T163000 DTEND;TZID=America/Los_Angeles:20240410T172000 DTSTAMP:20240312T220422Z URL:https://escience.washington.edu/events/uwdss-incubator-3/ SUMMARY:UW Data Science Seminar: Winter Incubator DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Wednesday\, April 10th from 4:30 to 5:20 p.m. PST. The seminar will feature two proje cts from Jihyeon Bae and Hauke Schulz\, who participated in our 2024 Data Science Incubator program at the eScience Institute.\n2024 Spring Quarter seminars will be held in PAA A118 - campus map\n\n \;\n"Illuminating t he role of cold-pools in structuring shallow convection"\nAbstract: In ord er to develop a better parameterization of these clouds in our climate mod els\, we need to improve our understanding on how these different patterns of cloudiness form. Previous studies suggest that precipitation drastical ly influences these patterns\, in particular through the generation of so- called cold pools. These cold pools (marked in red in the satellite image) that are areas of cold air and form due to the evaporation of precipitati on are able to redistribute clouds by suppressing them within the cold poo l and generating new convection at their edges. The identification of thes e cold pools in satellite observations will provide valuable information t o better understand the formation of different cloud patterns and ultimate ly lead to an improved parameterization of shallow convection.\n\n\n"What do the leaders say? Analysis of the United Nations General Debate Corpus"\ nAbstract: In the first stage\, we pose a testable hypothesis: “How do d emocracies and autocracies frame the principle of sovereignty differently? ” Sovereignty is the most fundamental legal principle in the realm of gl obal governance\, developed to guarantee legally equal status among states and respect authority over territories. However\, authoritarian states ha ve invoked the sovereignty principle\, framing it as a free pass to enact any policies domestically. We aim to determine if there is any systematic difference in rhetorical usage between the two types of regimes\, using te xt analysis models. We use pre-trained static and dynamic models like GloV e and BERT to generate word-embeddings for each document.In the next stage \, we analyze not only what the leaders say\, but how they speak by employ ing computational linguistics models. Our goal is to unpack the preference s of authoritarian state leaders by mapping UNGD data to psychological mar kers. Linguistic Inquiry and Word Count (LIWC) generates dictionary-based measures of constructs that tap into linguistic styles. Using simple regre ssion and random forest model\, our prediction model hit 75% accuracy leve l of predicting regime type using linguistic features. This project is exp ected to contribute to the timely discussion on the growing political clou t of authoritarian regimes.\n\n\n\n\n\n\n\nThe UW Data Science Seminar is an annual lecture series at the University of Washington that hosts schola rs working across applied areas of data science\, such as the sciences\, e ngineering\, humanities and arts along with methodological areas in data s cience\, such as computer science\, applied math and statistics. Our prese nters come from all domain fields and include occasional external speakers from regional partners\, governmental agencies and industry.\n\n \;\n \nThe 2023-2024 seminars will be held in person\, and are free and open to the public.\n\n LOCATION:Physics/Astronomy Auditorium\, room A118\, Seattle\, WA\, X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Seattle\, WA\, ;X-APPLE-RAD IUS=100;X-TITLE=Physics/Astronomy Auditorium\, room A118:geo:0,0 END:VEVENT BEGIN:VEVENT UID:85@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240417T163000 DTEND;TZID=America/Los_Angeles:20240417T172000 DTSTAMP:20240415T162612Z URL:https://escience.washington.edu/events/uw-data-science-seminar-armeen- taeb/ SUMMARY:UW Data Science Seminar: Armeen Taeb DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Wednesday\, April 17th from 4:30 to 5:20 p.m. PST. The seminar will feature Armeen Ta eb\, an Assistant Professor in the UW Department of Statistics.\n\nThe sem inar will be held in the Physics/Astronomy Auditorium (PAA)\, Room A118 -  campus map.\n\n\n \;\n"Model Selection and False Positive Error Cont rol in Complex Modeling Paradigms"\nAbstract: Controlling the false positi ve error in model selection is a prominent paradigm for gathering evidence in data-driven science.  In model selection problems such as variable se lection and graph estimation\, models are characterized by an underlying B oolean structure such as presence or absence of a variable or an edge.  T herefore\, false positive error or false negative error can be convenientl y specified as the number of variables/edges that are incorrectly included or excluded in an estimated model.  However\, the increasing complexity of modern datasets has been accompanied by the use of sophisticated modeli ng paradigms in which defining false positive error is a significant chall enge.  For example\, models specified by structures such as partitions (f or clustering)\, permutations (for ranking)\, directed acyclic graphs (for causal inference)\, or subspaces (for principal components analysis) are not characterized by a simple Boolean logical structure\, which leads to d ifficulties with formalizing and controlling false positive error.  We pr esent a generic approach to endow a collection of models with partial orde r structure\, which leads to systematic approaches for defining natural ge neralizations of false positive error and methodology for controlling this error.  (Joint work with Peter Bühlmann\, Venkat Chandrasekaran\, and P arikshit Shah)\nBio: Armeen Taeb is an assistant professor in the Departme nt of Statistics at the University of Washington. His research interests l ie at the interface of optimization and statistics. His work currently foc uses on developing efficient methods for graphical and latent-variable mod eling\, learning provably optimal causal models from data\, domain adaptat ion\, and false positive error control in non-traditional settings. He is also interested in exploring the utility of statistical methodologies for real-world applications\, especially in the earth sciences. Prior to comin g to UW\, Armeen was a postdoctoral fellow of ETH Foundations of Data Sci ence (ETH-FDS) at ETH Zürich\, mentored by Peter Bühlmann. Previously\ , under the supervision of Venkat Chandrasekaran\, he obtained my PhD in the Department of Electrical Engineering at Caltech.\n\n\nThe UW Data Scie nce Seminar is an annual lecture series at the University of Washington t hat hosts scholars working across applied areas of data science\, such as the sciences\, engineering\, humanities and arts along with methodological areas in data science\, such as computer science\, applied math and stati stics. Our presenters come from all domain fields and include occasional e xternal speakers from regional partners\, governmental agencies and indust ry.\nThe 2023-2024 seminars will be held in person\, and are free and open to the public. LOCATION:Physics/Astronomy Auditorium\, room A118\, Seattle\, WA\, X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Seattle\, WA\, ;X-APPLE-RAD IUS=100;X-TITLE=Physics/Astronomy Auditorium\, room A118:geo:0,0 END:VEVENT BEGIN:VEVENT UID:86@escience.washington.edu DTSTART:20240425T003000Z DTEND:20240425T012000Z DTSTAMP:20240422T160003Z URL:https://escience.washington.edu/events/uw-data-science-seminar-joshua- agar/ SUMMARY:UW Data Science Seminar: Joshua C. Agar DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar event on Wedn esday\, April 24th from 4:30 to 5:20 p.m. PDT. The seminar will feature Jo shua C. Agar\, Assistant Professor Department of Mechanical Engineering an d Mechanics at Drexel University.\n\nThe seminar will be held in the Physi cs/Astronomy Auditorium (PAA)\, Room A118 – campus map.\n\n\n“Navigat ing the Data Deluge: AI\, Infrastructure\, and Decision-Making in the Era of Big Data”\nAbstract:\nScience has traditionally harnessed data to inf orm decisions. Historically\, data was sufficiently low-dimensional and ma nageable for human processing. However\, the rapid expansion of sensing te chnologies across disciplines has overwhelmed traditional human-centric me thods with vast\, high-velocity data streams from diverse and often unreli able sources. Despite the remarkable advances in computers and large langu age models like ChatGPT\, their capabilities remain limited. Current AI al gorithms predominantly excel in interpolation\, not extrapolation\, leadin g to unrealistic and nonsensical outputs when stretched beyond their train ing data.\n\nThis talk explores the intersection of massive data influx an d AI\, focusing on their limitations and potential in enhancing decision-m aking\, particularly in data-driven infrastructure. We propose a “humani stic carrot” – not the “stick” approach to address pressing challe nges in scientific data management\, spotlighting DataFed – a comprehens ive data management system. This platform facilitates autonomous pipelines for the curation\, sharing\, searching\, and fine-grain access control of data and metadata. We demonstrate how DataFed can streamline data managem ent for experimentalists\, enhancing data stewardship while reducing their workload.\n\nWe also delve into the intricacies of handling high-velocity data streams\, where gigabits per second of data necessitate immediate pr ocessing for critical decision-making or autonomous control. This section covers deploying high-availability inference servers for on-demand data an alysis and reduction. Additionally\, we explore the concept of AI co-desig n\, where algorithms are optimized to fit on programmable logic\, enabling rapid\, intelligent analysis\, decision-making\, and control on ultra-low cost\, low-power devices at unprecedented speeds. Finally\, we discuss th e broad applicability of these methodologies across various fields\, from particle physics to astronomy\, highlighting their potential to revolution ize our approach to data and AI integration.\n\n\nBiography: Dr. Joshua C. Agar is an Assistant Professor in the Department of Mechanical Engineerin g and Mechanics at Drexel University. With a foundational background in ex perimental materials science\, Dr. Agar is predominantly renowned for his pioneering contributions to AI algorithms\, computing infrastructure\, and the development of cyber-physical systems in the fields of materials synt hesis and microscopy. His expertise has been applied across a wide array o f disciplines\, including particle and plasma physics\, materials science\ , and fluid dynamics. An active member of various AI communities\, particu larly the FastML community\, which emphasizes ultra-low latency ML co-desi gn\, Dr. Agar has earned recognition as a leader in AI innovation. His wor k has garnered attention from prestigious institutions such as the Nationa l Academy of Engineering and the National Science Foundation.\n \;\nTh e UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data sci ence\, such as the sciences\, engineering\, humanities and arts along with methodological areas in data science\, such as computer science\, applied math and statistics. Our presenters come from all domain fields and inclu de occasional external speakers from regional partners\, governmental agen cies and industry.\n \; LOCATION:Physics/Astronomy Auditorium\, room A118\, Seattle\, WA\, X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Seattle\, WA\, ;X-APPLE-RAD IUS=100;X-TITLE=Physics/Astronomy Auditorium\, room A118:geo:0,0 END:VEVENT BEGIN:VEVENT UID:87@escience.washington.edu DTSTART:20240502T003000Z DTEND:20240502T012000Z DTSTAMP:20240426T161227Z URL:https://escience.washington.edu/events/uw-data-science-seminar-jihoon- lee/ SUMMARY:UW Data Science Seminar: Jihoon Lee DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar event on Wedn esday\, May 1st from 4:30 to 5:20 p.m. PDT. The seminar will feature Jihoo n Lee\, an MD-PhD candidate in the Medical Scientist Training Program at t he UW.\n\nThe seminar will be held in the Physics/Astronomy Auditorium (PA A)\, Room A118 – campus map.\n\n\n“Integrated analysis of plasma and single immune cells uncovers metabolic changes in individuals with COVID-1 9”\nAbstract:\nA better understanding of the metabolic alterations in im mune cells during severe acute respiratory syndrome coronavirus 2 (SARS-Co V-2) infection may elucidate the wide diversity of clinical symptoms exper ienced by individuals with coronavirus disease 2019 (COVID-19). Here\, we report the metabolic changes associated with the peripheral immune respons e of 198 individuals with COVID-19 through an integrated analysis of plasm a metabolite and protein levels as well as single-cell multiomics analyses from serial blood draws collected during the first week after clinical di agnosis. We document the emergence of rare but metabolically dominant T ce ll subpopulations and find that increasing disease severity correlates wit h a bifurcation of monocytes into two metabolically distinct subsets. This integrated analysis reveals a robust interplay between plasma metabolites and cell-type-specific metabolic reprogramming networks that is associate d with disease severity and could predict survival.\n\n \;\n\n\nBiogra phy: Jihoon Lee is an MD-PhD student at the UW. Jihoon’s research intere sts are in development of adoptive cell therapies for precise targeting of cancer\, and the use of systems biology to understand and improve these t herapies. His work has focused on integrated analyses of cell functional\, phenotypic\, and various layers of molecular data to infer critical molec ular changes that affect cell behavior. Jihoon was previously at Caltech\, where he obtained a BS in Bioengineering. He recently completed his PhD t raining and is now finishing up his MD training as part of the UW Medical Scientist Training Program.\n \;\nThe UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science\, such as the sciences\, engi neering\, humanities and arts along with methodological areas in data scie nce\, such as computer science\, applied math and statistics. Our presente rs come from all domain fields and include occasional external speakers fr om regional partners\, governmental agencies and industry.\n \; LOCATION:Physics/Astronomy Auditorium\, room A118\, Seattle\, WA\, X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Seattle\, WA\, ;X-APPLE-RAD IUS=100;X-TITLE=Physics/Astronomy Auditorium\, room A118:geo:0,0 END:VEVENT BEGIN:VEVENT UID:83@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240502T150000 DTEND;TZID=America/Los_Angeles:20240502T160000 DTSTAMP:20240305T221821Z URL:https://escience.washington.edu/events/aws-may24/ SUMMARY:AWS Cloud Workshop DESCRIPTION:UW’s Amazon Web Services (AWS) team holds a monthly workshop at the eScience studio hosted by AWS Senior Solutions Architect Joel Morga n. Rotating topics focus on best practices for research-centric infrastruc ture in the cloud.\n\nThursday\, May 2nd\, from 3:00 to 4:00 PM\, with hap py hour to follow.\nZoom registration link\nThe WRF Data Science Studio is located on the 6th floor of the Physics/Astronomy Tower on the UW campus: \nWRF Data Science Studio campus map\n LOCATION:eScience Institute WRF Data Science Studio\, 3910 15th Ave NE\, Se attle\, WA\, 98195\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, 98195\, United States;X-APPLE-RADIUS=100;X-TITLE=eScience Institute WRF Data Science Studio:geo:0,0 END:VEVENT BEGIN:VEVENT UID:88@escience.washington.edu DTSTART:20240509T003000Z DTEND:20240509T012000Z DTSTAMP:20240502T163944Z URL:https://escience.washington.edu/events/uw-data-science-seminar-ang-li/ SUMMARY:UW Data Science Seminar: Ang Li DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar event on Wedn esday\, May 8th from 4:30 to 5:20 p.m. PDT. The seminar will feature Ang L i\, Assistant Professor of Electrical and Computer Engineering at UW.\n\nT he seminar will be held in the Physics/Astronomy Auditorium (PAA)\, Room A 118 – campus map.\n\n"Tightly Integrated\, Programmable Hardware Accele ration"\n\nAbstract:\n\nThe slow-down of Moore's law and transistor perfor mance scaling have motivated specialized hardware accelerators that sacrif ice generality for higher performance and efficiency. Commodity accelerato rs (GPUs\, FPGAs\, etc.) that are attached to PCIe buses or connected over large networks have successfully accelerated several important applicatio ns such as artificial intelligence\, genome sequencing\, etc. However\, th e vast majority of applications cannot be easily accelerated with these sy stems due to the dynamic\, irregular control flows and data movements. Add ressing this challenge\, my research studies tightly integrated\, programm able accelerators that have very low communication overhead with the CPU p rocessors (i.e.\, system-on-chip). This enables a new computing paradigm c alled fine-grained acceleration\, which partitions an algorithm at functio n or loop body level\, executes each fragment on the most suitable process ing unit\, and minimizes the communication and orchestration overhead with novel hardware/software mechanisms.\n\n\n \;\n\n\n\nBiography:\n\nAng Li (he/his) is an Assistant Professor of Electrical and Computer Engineer ing at UW. He earned his B.Sc. in Electrical Engineering from Tsinghua Uni versity\, his M.A. in Electrical Engineering from Princeton University\, a nd his Ph.D. in Electrical and Computer Engineering from Princeton Univers ity. He directs the PN Computer Engineering Lab (PNCEL)\, which innovates from computing systems to semiconductor circuits and explores the interpla y between classic and emerging computing technologies.\n\nIn his doctoral research\, Dr. Li has developed a silicon-proven\, open-source\, FPGA rese arch and prototyping framework (PRGA) and studied tightly integrated\, man ycore-eFPGA\, system-on-chip (SoC) architectures. He has been a leading me mber in two multi-university teams who successfully taped out\, brought up \, and evaluated two silicon prototypes\, including a 2.2-billion-transist or\, Linux-capable\, fully cache-coherent\, manycore-accelerator-eFPGA SoC \, which is one of the biggest academic tape-outs to date.\n\n \;\nThe  UW Data Science Seminar is an annual lecture series at the University o f Washington that hosts scholars working across applied areas of data scie nce\, such as the sciences\, engineering\, humanities and arts along with methodological areas in data science\, such as computer science\, applied math and statistics. Our presenters come from all domain fields and includ e occasional external speakers from regional partners\, governmental agenc ies and industry.\n \; LOCATION:Physics/Astronomy Auditorium\, room A118\, Seattle\, WA\, X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Seattle\, WA\, ;X-APPLE-RAD IUS=100;X-TITLE=Physics/Astronomy Auditorium\, room A118:geo:0,0 END:VEVENT BEGIN:VEVENT UID:90@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20240522T163000 DTEND;TZID=America/Los_Angeles:20240522T172000 DTSTAMP:20260311T174408Z URL:https://escience.washington.edu/events/uw-data-science-seminar-ziheng- sun/ SUMMARY:UW Data Science Seminar: Ziheng Sun DESCRIPTION:Please join us for a UW Data Science Seminar event on Wednesday \, May 22nd from 4:30 to 5:20 p.m. PDT. The seminar will feature Ziheng Su n\, Research Associate Professor in the Center for Spatial Information Sci ence and Systems at George Mason University.\n\nThe seminar will be held i n the Physics/Astronomy Auditorium (PAA)\, Room A118 – campus map for PA A.\n\nGeoweaver for Improving Workflow Tangibility and Reducing Research A nxiety\n\nAbstract:\n\nIn this talk\, we will together explore the transfo rmative potential of Geoweaver\, a productivity workflow management tool\, in enhancing the tangibility of research workflows and mitigating researc h anxiety. It allows you to streamline complex research processes\, provid ing intuitive interfaces and seamless integration of computational tasks. By fostering a more structured and manageable approach to research\, it em powers researchers to navigate sophisticated workflows with confidence and efficiency\, ultimately advancing scientific inquiry across diverse domai ns. Join us to discover how Geoweaver revolutionizes research practices\, promoting clarity\, productivity\, and innovation. More details can be fou nd at Geoweaver.\n\nBio: Dr. Ziheng Sun is a research associate professor at George Mason University. He is the PI of NASA ACCESS Geoweaver project\ , and NSF Geoinformatics project. He has worked on scientific workflow man agement for many years and published over 100 papers and book chapters. He is the chair of ESIP machine learning cluster and currently an AI practit ioner trying to answer challenging Earth science questions with the latest technologies.\n\n \;\n\nThe UW Data Science Seminar is an annual lect ure series at the University of Washington that hosts scholars working acr oss applied areas of data science\, such as the sciences\, engineering\, h umanities and arts along with methodological areas in data science\, such as computer science\, applied math and statistics. Our presenters come fro m all domain fields and include occasional external speakers from regional partners\, governmental agencies and industry.\n END:VEVENT BEGIN:VTIMEZONE TZID:America/Los_Angeles X-LIC-LOCATION:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20220313T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20221106T010000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST END:STANDARD BEGIN:DAYLIGHT DTSTART:20230312T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20231105T010000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST END:STANDARD BEGIN:DAYLIGHT DTSTART:20240310T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT END:DAYLIGHT END:VTIMEZONE END:VCALENDAR