Student Fellows

(project description available here)

 

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Abhilash Biswas, Fellow

Graduate Student
Heinz College, Carnegie Mellon University

Website

Project: Satellite Streaks in Astronomical Images

Abhilash is currently pursuing an MS in Public Policy and Data science at Carnegie Mellon University. Prior to this, he was working at a global non-profit called IDinsight where he worked with decision makers in the development sector in India to conduct statistical evaluations and provide data driven evidence for informed decision making. As a part of his work, Abhilash supported the monitoring and evaluation of flagship government welfare programs in India.

Abhilash has a keen interest of applying public interest technology towards social impact, aimed at better optimization and delivery of welfare services in resource constrained developing countries. At the DSSG fellowship, Abhilash is keen to learn rigorous data science skills and is greatly looking forward to analyzing outer space image data. 

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Kilando Chambers, Fellow

Undergraduate Student, Applied Mathematics and Psychology
Harvard University

Website

Project: Satellite Streaks in Astronomical Images

Kilando Chambers (he/him/his) is a rising senior and assistant researcher at Harvard University studying Applied Mathematics and Psychology. Chambers studies how to design computational tools for his lab that perform automatic statistical analyses on the link between childhood trauma and stigmatization. Outside of his research and academic endeavors, Kilando is a tutor and creates free lessons and workshops on topics ranging from Income Inequality to Neurodivergence.

Kilando is a low-income first-generation black student from Mississippi. Social good and data have always been integrated into his life. In the future, Kilando intends to pursue a career in data science that is beneficial to minoritized people worldwide. He is excited to work with the DSSG program to further his passions in these areas.

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Vidisha Chowdhury, Fellow

Master’s Student, Heinz College of Information Systems and Public Policy
Carnegie Mellon University

Website

Project: Heating Loads in Alaska and Beyond

Vidisha is passionate about using data-based insights to drive social impact and has a multidisciplinary approach to problem solving. She is pursuing her second master’s degree in Data Analytics, Public Policy and Management at Heinz College, Carnegie Mellon University. Her most recent work applies natural language processing to social media data to find effective ways of creating mental health awareness.

While in India, she completed a master’s degree in Economics at the Delhi School of Economics and interned for companies like IBM and TCS. This got her interested in applying data-science to improve decision-making. Later, she worked at the Indian Statistical Institute, Delhi for two years, on a project that evaluated the impacts of induction stoves on air pollution in rural India.

Her work experience and her coursework in environmental policy at Heinz helped her understand the disproportionate effects of climate change on various communities. Hence, as a DSSG fellow, she intends to contribute to climate justice by helping improve methods of thermal energy use estimation and informing decarbonization strategies in the Arctic region. She is particularly eager to work with geospatial big data as a part of this project.

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Madelyn Gaumer, Fellow

Master’s Student, Department of Applied Mathematics
University of Washington

Website

Project: Heating Loads in Alaska and Beyond

Madelyn is currently getting her master’s degree in applied and computational mathematics through the Applied Mathematics Department at the University of Washington. Madelyn received her bachelor of science in Mathematics from Harvey Mudd College. Prior to her graduate work, Madelyn worked as a data scientist at Pacific Northwest National Laboratory (PNNL)  and as a software engineer at Microsoft. She enjoys working on problems in the fields of optimization, machine learning, computer vision, and natural language processing.

Beyond her technical interests, Madelyn is very passionate about social justice issues, particularly those in STEM education. While working at PNNL, she worked as a STEM ambassador, teaching the public about research and showcasing the diversity of scientists at PNNL. Overall, Madelyn has a passion for using computer science and mathematics to solve interesting and socially relevant problems, which led to her interest in the DSSG program.

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Zhaowen Guo, Fellow

Ph.D. Candidate, Political Science
University of Washington

Website

Project: Tracking family and intergenerational poverty using administrative data

Zhaowen Guo is a Ph.D. candidate in political science and a consultant at the Center for Social Science Computation and Research (CSSCR) at the University of Washington. Prior to joining the University of Washington, she holds a master’s degree in political science at Columbia University with Chinese Government Scholarship, and a bachelor’s degree in political science at Fudan University.

Her research agenda has centered around how information and technology impact public discourses, government accountability, and political behavior. Her dissertation is exploring how a surveillance society takes root and its consequences on welfare provision and political participation in China. She is looking forward to participating in the DSSG program to leverage her inter-disciplinary experiences in data science and social science in solving real-world problems.

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Ihsan Kahveci, Fellow

Ph.D. Student, Sociology
University of Washington

Website

Project: Tracking family and intergenerational poverty using administrative data

İhsan is a third-year doctoral student in Sociology at the University of Washington and an affiliated student at the Max Planck Institute for Demographic Research. He holds an MA in Sociology from the University of Washington and a BA in Management from Bogazici University, Turkey.

İhsan’s research focuses on the intersection of public health and social networks. His mixed methods research integrates computational sociology, demography and social epidemiology. His dissertation focuses on vaccine-hesitancy and health misinformation, especially in non-Western contexts. His work also considers the religious and political dynamics behind adherence to COVID-19 public health measures.

İhsan is extremely motivated to use his scientific knowledge and data science skills to solve real-life social problems. DSSG and WMLAD are excellent initiatives to pursue this goal, and he is excited to be part of these dynamic teams. In his free time, İhsan enjoys stand-up comedy and swing dancing. He also performs irregularly at open mics.

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Aziza Mirsaidova, Fellow

Master’s Student, Artificial Intelligence, McCormick School of Engineering 
Northwestern University

Website

Project: Exploring new understandings of the cost of living at a basic needs level using the Self-Sufficiency Standard database

Aziza Mirsaidova is a Master’s student at Northwestern University, McCormick School of Engineering. She is pursuing her studies in Artificial Intelligence with a focus on Natural Language Processing and Understanding. She is interested in learning and researching computational approaches that enable computers to understand human language and break down communication barriers between people and language technologies. At Northwestern, she is involved in multiple research projects including Tiilt lab where she is involved in enhancing the source separation process for the Blinc app and leading user research study groups to understand and improve the student’s collaboration process using AI integrated technologies.

During the summer before pursuing her master’s degree, Aziza was nominated as a Station1 Frontier Fellowship Scholar where she was trained as Research Scientist to conduct socially directed science and technology research. As a part of her fellowship, she was a Data Science Research Intern at GreenInfo Network. She investigated and analyzed the living patterns and land of contemporary Ohlone People in the Bay Area, California using Geospatial Information System mapping tools, and other statistical methods. She aims to integrate her technical skills and understanding, and practical implementation of AI techniques in projects with a positive impact to society and is excited to join DSSG program this summer.

Outside of academics, she is an epee fencer, language learner and amateur traveler.

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Betelhem Aklilu Muno, Fellow

Master of Public Health Student in Epidemiology
School of Public Health, University of Washington

Website

Project: Tracking family and intergenerational poverty using administrative data

Betelhem Muno is an incoming Master of Public Health (MPH) student based out of the department of Epidemiology in the School of Public Health at University of Washington (UW). She is excited to start in the fall with the hopes of focusing on maternal and child health through an epidemiological lens. She just completed her undergraduate degree at Haverford College with a major in Environmental Studies (focusing on Environmental Health) and a minor in Health Studies. Her understanding of the ways data impacts health policies and health outcomes-in all aspects of life-pushed her to start taking data science courses to become equipped with the analytical tools needed to interpret and comprehend data. She intentionally focuses all of her work on health issues that impact under-resourced communities, especially issues that impact Black communities both in the U.S. and globally. Her interest in the intersection of data science and public health issues, and seeing the ways economical health influences every other form of health prompted her to join DSSG and her project, respectively.

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Priyana Patel, Fellow

Master’s Student, Human Centered Design and Engineering
University of Washington

Website

Project: Exploring new understandings of the cost of living at a basic needs level using the Self-Sufficiency Standard database

Priyana is a Master’s student in the Department of Human Centered Design and Engineering at the University of Washington. She earned her B.S. in Cognitive Science with a Specialization in Computing and a Minor in Digital Humanities from the University of California, Los Angeles (UCLA). Her work in her graduate program focuses on engaging in a deep critical analysis of society and challenging the landscape of design systems, ethics, and equity in a people-first environment. Some of her projects include a mobile AR game for middle schoolers to evaluate online misinformation and a virtual wayfinding system for museum visitors with sensory processing challenges. She is excited to participate in DSSG and explore poverty evaluation and income inequality in the Self-Sufficiency Standard. She is particularly interested in working with diverse stakeholders and considering how converging identities, such as race, gender, and disability status, influence the poverty metric.

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Cheng Ren, Fellow

Doctoral Student, Berkeley School of Social Welfare
University of California

Website

Project: Exploring new understandings of the cost of living at a basic needs level using the Self-Sufficiency Standard database

Cheng Ren (he/his/him) is a Ph.D. student in Social Welfare and Data Science at the University of California, Berkeley. He is also a Senior Data Science Fellow at D-Lab at UC Berkeley. Prior to Berkeley, he earned his master’s degree at Case Western Reserve University in Social Work and then worked as a data scientist in several social welfare related projects.

Cheng is interested in nonprofit development, housing, and computational social welfare. Her current dissertation uses computational methods, especially natural language processing, to collect, analyze, estimate and visualize the eviction crisis in the United States.

Cheng is excited to learn data science integrated with various fields for social good this summer. He looks forward to learning from other fellows and contributing to the program in poverty measurement empowered by new techniques.

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Ashley Santos, Fellow

Undergraduate Student, Computing, Data Science and Society Department
University of California, Berkeley

Website

Project: Satellite Streaks in Astronomical Images

Ashley Santos is a first-generation Latina-identifying undergraduate student at the University of California, Berkeley where she is studying Data Science with an emphasis in Business/Industrial Analytics. She also earned two Associates degrees in Mathematics and Liberal Arts: Social and Behavioral Sciences at Berkeley City College.

Prior to DSSG, she was a research assistant alongside a UC Berkeley Ph.D. student where she cleaned and constructed data visualizations to summarize statistical data for a donor presentation in order to fund and continue research on COVID-19 impacts in India.

Ashley is passionate about social justice and equity and hopes to use data science principles to address the structural inequities she has witnessed growing up. She is fascinated about how data science principles can contribute to a better understanding of the world and come down to data-driven conclusions. She was drawn to DSSG because of the program’s commitment to social good and the opportunity to refine her data science technical skills for a project that matters.

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Philippe Schicker, Fellow

Master’s Student, Heinz College of Information Systems and Public Policy
Carnegie Mellon University

Website

Project: Heating Loads in Alaska and Beyond

Philippe Schicker (he/his) is a master’s student at Carnegie Mellon University studying public policy and data analytics with a focus on environmental policy and justice. Philippe holds a bachelor’s degree in mechanical engineering and has published multiple peer-reviewed papers on sustainable engineering solutions. Philippe has attended universities in Los Angeles, CA, Starkville, MS, and Pittsburgh, PA to study environmental impacts on different regions of the United States. He continued his education to supplement his technical engineering education with quantitative policy and data analysis tools to better combat climate change and advocate for environmental justice.

Philippe was particularly attracted to the DSSG fellowship for its emphasis to combine rigorous data science techniques with current societal problems. He aims to use his skills and the exposure to continue working on climate change solutions. Therefore, the project related to estimating thermal energy use in Arctic regions which can be used as part of decarbonization planning was particularly exciting to Philippe, allowing him to work the very pressing problem that is climate change. He aspires a career in public service and is looking forward to working with the team on this DSSG project.

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Shamsi Soltani, Fellow

Doctoral Student, Department of Epidemiology and Population Health, School of Medicine
Stanford University 

Website

Project: Heating Loads in Alaska and Beyond

Shamsi is a public health professional and scholar pursuing a PhD in Epidemiology and Clinical Research at Stanford University. Her past work includes transportation injury surveillance and COVID emergency response at the county level, as well as clinical trials, program evaluation, and community based HIV prevention. Currently she’s exploring how to use big data methods with an equity focus, and is excited to experience production level coding in a team environment via DSSG. Shamsi holds an MPH in Epidemiology from Tulane University School of Public Health & Tropical Medicine, and a BS in Neuroscience with French minor from UCLA. She is a multicultural, multilingual first-gen American who likes to read copiously for pleasure, get outdoors, dance, bike and– occasionally, when the mood strikes­– bake elaborate meringues.

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Hector Joel Sosa, Fellow

Ph.D. Student, Social Psychology
University of Massachusetts – Amherst

Website

Project: Exploring new understandings of the cost of living at a basic needs level using the Self-Sufficiency Standard database

Hector Joel Sosa is an Ph.D. Student in the Social Psychology program at the University of Massachusetts – Amherst. Originally from Brooklyn, NY, he holds an undergraduate degree in Psychology from the University at Buffalo. As a former McNair Scholar and student in the Educational Opportunity Program, Hector’s research focuses primarily on supporting members of underrepresented/underserved groups succeed in STEM while in college. Recently, he has explored how cultural alignment or mismatch between individuals’ goals (agentic vs. communal) and perceived goals of STEM (STEM promotes more agentic vs. communal goals) is associated with individuals’ interest in STEM majors.

Hector is excited to be a part of the DSSG program to utilize machine learning techniques to address the cost of living. This program will allow him to develop his technical skills while also addressing a social issue that is relevant to some lived experiences.

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Eliot Stanton, Fellow

Recent Graduate, Data Science and Analytics
Simmons University

Website

Project: Tracking family and intergenerational poverty using administrative data

Eliot (they/them) is a new graduate of Simmons University in Boston, where they studied data science. They enjoy conducting all manners of data exploration and visualization, especially using R. While at Simmons, Eliot also completed a theoretical gender studies thesis entitled “Binaries in Binary: Harmful Consequences and Radical Possibilities of Technology for Trans Liberation” and presented their work as a Keynote Speaker at the Simmons Undergraduate Symposium. During part of a COVID gap year, Eliot worked as a Civic Digital Fellow at the U.S. Census Bureau, and they have also interned at Bluebonnet Data and Bank of America. Eliot was initially interested in DSSG for the opportunity to apply technical skills in service of a meaningful cause, and they are extremely excited to work on the challenge of tracking poverty through a complex dataset. They’re also looking forward to close teamwork, mentorship, and engaging with ethical issues.

 

 

Project Leaders

(project description available here)

 

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Dino Bektešević, Project Lead

Graduate Student, Astronomy Department
University of Washington

Project: Satellite Streaks in Astronomical Images

My research projects focus on facilitating and accelerating science. I do this by leveraging knowledge and algorithms from different fields in ways they have not yet been in Astronomy or by creating tools that allow others to do science easier, faster or more affordably. My previous work was on the Vera C. Rubin Observatory Proof of Concept Team that executed their image and catalog processing pipelines, on cloud services. Cloud services enable researchers to elastically deploy and/or supplement compute and storage resources on a pay-as-you-use model which can significantly reduce total costs for short term (1 to 3 years) projects that involve large scale astronomical data reduction. An area that has recently interested me a lot is classification of astronomical objects from their light curves. By borrowing elements from Riemannian geometry and statistical inference, we are able to describe shapes of curves and define the concept of distance between them. This allows us to cluster and categorize light curves of objects without requiring, or having, any other information.

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Nicholas Bolten, Project Lead

Data Science Postdoctoral Fellow, eScience Institute
University of Washington

Project: Heating Loads in Alaska and Beyond

My research focuses on the intersection between pedestrian mobility, data science, and computer science. I work on defining, collecting, producing user-facing tools for, and analyzing pedestrian network data – data that is otherwise rarely collected but exposes serious inequities and accessibility concerns in our public spaces. My PhD work focused on two projects, OpenSidewalks and AccessMap. OpenSidewalks is a project for openly defining, creating, and analyzing pedestrian network data, particularly in OpenStreetMap. AccessMap is a user-facing information retrieval tool, an interactive map that adapts to an individual’s preferences when navigating the built environment: if a person requires curb ramps, it will avoid raised curbs and if a person cannot go up steep hills, it will avoid them, while still providing a realistic path from a start point to an end point. My current research extends on these projects to include a larger number of cities, promote integration between municipalities and OpenSidewalks datasets, and understand pedestrian accessibility on city and regional scales. Both AccessMap and OpenSidewalks have participated in DSSG projects (on the project side!) that pushed them to the next level and I’m excited to be on the other side of the equation: supporting DSSG work as a data scientist.

Dharma Dailey, Human Centered Design Mentor

Data Science Postdoctoral Fellow
University of Washington

Dharma Dailey is a UW Data Science Postdoctoral Fellow at the eScience Institute working with research scientist Anissa Tanweer to understand how human centered design practices can be incorporated into data intensive research. She is the Human Centered Design Mentor for eScience’s Data Science for Social Good Program. She coaches DSSG teams to explore the social dimensions of their projects as a team, interact with stakeholders, and integrate that awareness into project work. She is also working with a coalition of Data for Good organizers to document better practices for running Data Science for Social Good Programs.

Her PhD research focused on the use of social media during crises with special attention to how information of value to crisis-affected communities is produced and diffused. That line of research has given her an appreciation for the value of integrating interpretivist approaches and human-centered methods into computational social science projects.
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Jessica Godwin, Data Scientist 

Statistical Demographer + Training Director, Center for Studies in Demography & Ecology
University of Washington

Website

Project: Tracking family and intergenerational poverty using administrative data

Jessica is a Statistical Demographer and the Training Director for the Center for Studies in Demography & Ecology (CSDE) at the University of Washington. Their roles include support and training for CSDE students pursuing demographic and population research and providing consulting in statistical and demographic methods to CSDE faculty affiliates and students. Their broad research interests include demographic methods, Bayesian spatiotemporal methods, survey statistics, and the places where all of those things overlap. Jessica is passionate about teaching, mentorship, and research applications that improve the lives of people and communities, all things fundamental to DSSG! Jessica received her Ph.D. from the Department of Statistics at the UW and is a former CSDE Trainee and Fellow. Born and raised in Alabama, they received their M.S. in Statistics and B.S. in Actuarial Science at Auburn University. War eagle!

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Bryna Hazelton, Data Scientist 

Senior Research Scientist, Physics Department and eScience Institute
University of Washington

Project: Exploring new understandings of the cost of living at a basic needs level using the Self-Sufficiency Standard database

Bryna Hazelton is a Senior Research Scientist in the Physics Department and the eScience Institute. Bryna’s primary research is in astrophysics and cosmology, she helps design and build telescopes to detect signatures of the first stars and galaxies forming 13 billion years ago. She is an expert in the statistical analysis of peta-byte scale data from these telescopes, trying to detect an incredibly faint signal from the early universe in the face of very bright foreground galaxies and subtle instrumental systematics.

Bryna received her PhD in Physics from UC Santa Cruz in 2009, where she used satellite, airborne and ground-based instruments to study x-ray and gamma-ray emissions from thunderstorms. She also holds an MS in physics from UCSC and a BS in physics from UC San Diego. She came to UW as a postdoctoral researcher in 2009 to study astrophysics and cosmology with custom-built radio telescopes. Bryna is the lead developer and maintainer of several widely used astronomical and cosmological open source packages.

Bryna joined the eScience Institute in April, 2015 and has been very involved in DSSG and the Incubator ever since. Bryna really enjoys learning about challenges in new fields and enjoys bringing her skills in statistical analyses, SQL databases and open source software development to bear in new projects.

Bernease Herman, Data Scientist

Bernease Herman, Data Scientist

Data Science Fellow, eScience Institute
University of Washington

Data Scientist At-Large

Bernease Herman joins the eScience Institute as a Data Scientist. Bernease was most recently a Software Development Engineer at Amazon, where she collaborated with operations research scientists and statisticians to add economic constraints and buying models to Amazon’s Inventory Planning and Control system. Previous to Amazon, Bernease worked on derivatives pricing and predictive modeling at the research arm of Morgan Stanley. Bernease earned her BS in Mathematics and Statistics from the University of Michigan.

Vaughn Iverson, Data Scientist

Vaughn Iverson, Data Scientist 

Research Scientist, eScience Institute
University of Washington

Website

Project: Satellite Streaks in Astronomical Images

Vaughn Iverson is a Senior Research Scientist with the Center for Environmental Genomics in the UW School of Oceanography, where his research involves developing biological sensing methods capable of inferring the behaviors and interactions within natural microbial communities by identifying and quantifying genes and proteins used by specific members of the community (metagenomics and metatranscriptomics).

Vaughn joined the eScience Institute in January of 2016 and contributes expertise in development of high performance parallel software, web technologies, noSQL databases, and data compression and visualization techniques. Vaughn is the author and maintainer of several popular open source packages and is an active contributor to many others.

Vaughn earned his PhD in Biological Oceanography from the University of Washington in 2015, and also holds a MS in Computer Science from the University of Washington, Seattle and a BS in Computer Science and Chemistry from Washington State University, Pullman. Prior to commencing his PhD work, Vaughn spent over a decade in the computer industry working for Intel Corp as a Staff Research Scientist developing video compression, internet media streaming and content distribution technologies, for which he was awarded twenty US patents.

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Annie Kuclick, Project Lead

Research Coordinator, Center for Women’s Welfare, School of Social Work
University of Washington

Project: Exploring new understandings of the cost of living at a basic needs level using the Self-Sufficiency Standard database

Annie Kucklick is a social worker and researcher focused on economic mobility. She is the lead author on the Center for Women’s Welfare’s published. She steers engagement with national and state partners, including presentations on the Standard, press release consultation, and new partner development. Prior to her position with the Self-Sufficiency Standard, Annie supported the economic justice project at the Washington State Coalition Against Domestic Violence, ran multiple local campaigns in the Seattle area, and investigated corporate abuse in conflict zones. In 2013, she worked as a research fellow with the Karen Human Rights Group along the Thai-Burma border. Annie received a Master of Social Work—Administration and Policy Practice from the University of Washington in 2020.

Annie is thrilled to participate in the DSSG summer project and learn about innovative methods in data infrastructure and hosting. She is even more excited about the end result–having a consolidated database of Self-Sufficiency Standard data for all the states and years it’s been in production.

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Lisa Manzer, Project Lead

Director, Center for Women’s Welfare, School of Social Work
University of Washington

Project: Exploring new understandings of the cost of living at a basic needs level using the Self-Sufficiency Standard database

Lisa Manzer is Director of the Center for Women’s Welfare University of Washington School of Social Work. Since 2007, she has been leading collaborations with Self-Sufficiency Standard partners as well as developing new methodology and analysis utilizing the Self-Sufficiency Standard. Lisa earned a Master of Public Administration degree from the Evergreen State College with a concentration on poverty policy. In addition to a background on performance measurement and reporting, Lisa has spent most of her career in research on projects ranging from issues of poverty policy, positive youth development, and recycling behavior. She is really excited to be participating in the DSSG program to learn more data science best practices and is looking forward to collaborating with the students.

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Meredith Rawls, Project Lead

Research Scientist, Department of Astronomy; Data-intensive Research And Cosmology (DiRAC)
University of Washington

Website

Project: Satellite Streaks in Astronomical Images

Meredith Rawls is a research scientist in the Department of Astronomy at the University of Washington and the Institute for Data-intensive Research And Cosmology (DiRAC). She writes software and data pipelines to handle terabytes of nightly images from Vera C. Rubin Observatory’s Legacy Survey of Space and Time, which will produce the highest resolution movie of the night sky ever made. Her background is in stellar astrophysics, and she earned her PhD from New Mexico State University.

Since early 2020, Meredith has studied the plethora of newly-launched commercial satellites in the hopes observers worldwide don’t lose the sky. She has served on and chaired working groups and co-authored reports for multiple workshops on astronomy and satellite constellations, and is spearheading the SatHub initiative at the new International Astronomical Union Centre for the Protection of the Dark and Quiet Sky from Satellite Constellation Interference (IAU CPS). The broad impacts of a hugely increasing satellite population motivated her to lead a DSSG project team with Dino Bektešević, and she is looking forward to working with students to better quantify the situation and build tools that can help astronomers alongside other stakeholders as we all grapple with rapidly changing skies.

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Jennie Romich, Project Lead

Associate Professor, School of Social Work
University of Washington

Project: Tracking family and intergenerational poverty using administrative data

Jennie Romich is a Professor of Social Welfare at the UW School of Social Work and Faculty Director of the West Coast Poverty Center. Romich’s research focuses on poverty, low-paid workers, and families’ interactions with public policy. Her recent projects include mixed-method evaluations of the Seattle Paid Safe and Sick Time Ordinance and $15 minimum wage.  She co-leads the national effort on “Reducing Extreme Economic Inequality” for the American Academy of Social Work & Social Welfare’s Grand Challenges Initiative and co-chairs a national research network on “Poverty, Employment, and Self-Sufficiency” through the U.S. Collaborative of Poverty Centers.

As the principal investigator of the Washington Merged Longitudinal Administrative Data and DSSG ’21 alum, Romich is excited to again work with the DSSG summer project as a way of learning more about data science techniques applicable to large-scale administrative data set.

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Erin Trochim, Project Lead

Research Assistant Professor, Alaska Center for Energy and Power
University of Alaska Fairbanks

Website

Project: Heating Loads in Alaska and Beyond

Erin is a geospatial data scientist with a strong interest in decision making focused on energy and northern applications. She received her interdisciplinary PhD from the University of Alaska Fairbanks with a focus on Remote Sensing & Hydrology. Her postdoc with the Alaska Climate Adaptation Science Center included work with the NSF SEARCH program to make permafrost information accessible for policy applications. Currently, her projects focus on energy needs in Alaska including the Arctic Energy Atlas (AEA), creating environmental data for marine and hydrokinetic applications and the Railbelt Decarbonization study. The DSSG heating loads project will provide key information for both the decarbonization and AEA work.