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UID:235@escience.washington.edu
DTSTART;TZID=America/Los_Angeles:20241022T163000
DTEND;TZID=America/Los_Angeles:20241022T172000
DTSTAMP:20241112T201308Z
URL:https://escience.washington.edu/events/uw-data-science-seminar-curtis-
 atkisson/
SUMMARY:UW Data Science Seminar: Curtis Atkisson with Jihyeon Bae & Daniel 
 Vogler
DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Tuesday\, O
 ctober 22nd from 4:30 to 5:20 p.m. PT. The seminar will feature Curtis Atk
 isson\, a Data Scientist at the UW eScience Institute along with Jihyeon B
 ae\, Ph.D. Candidate in Political Science\, and Daniel Vogler\, Master's S
 tudent in Data Science at the University of Washington.\n\nThe seminar wil
 l be held in the Physics/Astronomy Auditorium (PAA)\, Room A118 - campus 
 map.\n\n\n&nbsp\;\n"Serving client-side computation on a static server: We
 bAssembly"\nAbstract: WebAssembly is a new tool that offers the opportunit
 y to deliver efficient\, high-performance programs to diverse hardware (li
 ke your laptop) consistently. This results in a program that is delivered 
 via a web page and then runs on a local machine. As in\, whoever writes th
 e code can use a static server to deliver dynamic results. WebAssembly is 
 an instruction format for computers (i.e.\, the thing that translates a co
 mputer programming into something that is machine readable) that uses reso
 urces provided by the browser to execute code. There are a number of reaso
 ns we might want to do this including economics (you don’t have to pay f
 or a server)\, philosophy (all programs should always be accessible)\, and
  user experience (cross-compatibility). This comes with problems\, though\
 , namely security\, which the community has worked hard to counteract. One
  of the primary benefits of WebAssembly is that\, as a binary format\, it 
 is able to glue together many different software languages\, each of which
  has been optimized in different ways and has communities with different i
 nterests. This allows us to use highly performant libraries and packages\,
  no matter the language in which they are written\, using JavaScript as th
 e glue. Such programs are also web native with little adjustments. WebAsse
 mbly is a highly flexible tool that all developers and data scientists sho
 uld know to efficiently and effectively deliver to a variety of stakeholde
 rs.\nBio: Curtis Atkisson joined the eScience Institute in Feb 2024. He re
 ceived his PhD in Evolutionary Anthropology from UC Davis with a designate
 d emphasis in Computational Social Science. His dissertation was on how ch
 anges in people’s complex social networks impact their cooperative behav
 ior. This work involved ethnography\, participant observation\, and survey
 s done amongst the Makushi (and some Wapashana) in southern Guyana. The an
 alysis of those data required complex networks\, designing new measures of
  information in those networks\, and modeling those changes with custom-bu
 ilt Bayesian statistical models. His postdoctoral work applied his methodo
 logical expertise to understanding Open Source Software communities and ho
 w they persist\, as well as expanding his tools to include Text As Data/Te
 xt Mining\, machine learning\, and AI approaches to understanding text (e.
 g.\, GPT as a zero-shot translator). Substantively\, Curtis is interested 
 in why people cooperate with others\, or\, perhaps more accurately\, why w
 e do not always cooperate with others. This ranges from small-scale cooper
 ation such as sharing food with a neighbor up to large-scale cooperation s
 uch as building computer software that we give away for free that makes ot
 her people rich. He is also interested in using open-source software as a 
 model system to study many processes in the social sciences–due to the n
 ature of open-source software\, almost all of the data regarding interacti
 ons within and participation in the system are publicly available.\nJihyeo
 n Bae is a PhD candidate in the Political Science Department at the Univer
 sity of Washington. She is interested in comparing design choices around i
 nternational organizations and how they influence cooperation among states
 . She is also passionate about applying NLP models to explore how rhetoric
  changes in international forums like the United Nations General Assembly.
  During the UW DSSG program\, she will work on a project assessing water r
 euse patterns\, based on substantive knowledge in actor-based institutiona
 l design. Born and raised in South Korea\, she received her B.A. in Intern
 ational Studies from Kyung Hee University in 2019\, with additional traini
 ng from the Applied Mathematics Department.\nDaniel Vogler currently pursu
 ing a Master’s degree in Data Science at the University of Washington. B
 efore graduate school he worked as a management consultant\, primarily sup
 porting clients in healthcare and retail. Daniel graduated with a B.A. fro
 m Princeton University in 2021. He is deeply interested in the intersectio
 n between data science\, machine learning\, and energy\, especially in dat
 a-driven approaches to energy policy.\n\n\nThe UW Data Science Seminar is
  an annual lecture series at the University of Washington that hosts schol
 ars 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 statistics. Our pres
 enters come from all domain fields and include occasional external speaker
 s from regional partners\, governmental agencies and industry.\n&nbsp\;\n\
 nThe 2024-2025 seminars will be held in person\, and are free and open to 
 the public.
ATTACH;FMTTYPE=image/jpeg:https://escience.washington.edu/wp-content/uploa
 ds/2024/02/Curtis_Atkisson_cropped-scaled.jpg
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
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DTSTART:20240310T030000
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