DSSG 2023 Student Fellows group photo.

Meet the DSSG 2023 Teams

The eScience Institute’s annual Data Science for Social Good (DSSG) program kicks off next week, and we are excited to host a new group of Student Fellows at the WRF Data Science Studio throughout the summer. 2023 marks the ninth year of DSSG, and two teams will spend the next ten weeks collaborating with our data scientists on projects that help them apply data science tools to larger social issues. This year’s cohort will bring together a wonderfully diverse group from all over the country.

“Heating Pumps in Alaska and Beyond”


Erin Trochim, Project Lead

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

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 cost estimates of transmission lines across the pan-Arctic, creating environmental data for marine and hydrokinetic applications and the Railbelt Decarbonization study. Erin is excited to return to the DSSG program to follow-up with developing estimates for heating and cooling needs in Alaska using heat pumps.


Madelyn Gaumer, Data Scientist

Data Scientist, Pacific Northwest National Laboratory

Madelyn is currently a data scientist at Pacific Northwest National Laboratory (PNNL), where she has been since 2019. She works in the fields of computer vision, deep learning, optimization, and natural language processing. Prior to working at PNNL, Madelyn worked as a software engineer at Microsoft. Madelyn earned 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.

Aminat Adefolu, Student Fellow

Central Michigan University

Aminat is currently pursuing her doctoral degree in a field related to applied statistics and data science. Her educational background includes a bachelor’s degree in mathematics and statistics, master’s degree in data analytics, where she developed a strong foundation in programming and data analysis. With a passion for using data to drive social change, she has
actively engaged in research projects that involve leveraging data science techniques to address real-world problems.

Silas Gifford, Student Fellow

University of California, Berkeley

Silas Gifford believes in the transformative power of data science for new fields and applications and is particularly interested in the intersection of the environment, society, and machine learning. Since summer 2021, Silas has been working on a proof of concept project for monitoring seals at Point Reyes National Seashore using deep learning and aerial imagery. Silas is a Golden Bear through and through, having completed an undergraduate degree in Data Science at UC Berkeley and is now working towards a Master of Information and Data Science degree from the School of Information.

Katherine Grisanzio, Student Fellow

Harvard University

Katherine received her B.S. in Psychology from Boston College, then spent four years as a Lab Manager in the Psychiatry Department at Stanford University. Now, she is a PhD student in the Cognition, Brain, & Behavior program with a secondary field in Data Science at Harvard University. Katherine’s research focuses on leveraging behavioral, longitudinal, and neuroimaging techniques to characterize emotional experiences across adolescent development and identify critical brain-behavior relationships during this transitional age period.

Brian Leung, Student Fellow

University of Washington

Brian Leung is a PhD student in the Department of Political Science at the University of Washington. His research interests include the political economy of industrial policy, supply chain and reshoring in emerging technologies, and violence and repression in authoritarian regimes. He is also interested in a wide range of quantitative methods, particularly causal inference, survey experiments, and quantitative text analysis. Born and raised in Hong Kong, he received his Bachelor of Social Sciences and Bachelor of Laws from the University of Hong Kong in 2017.  

“Generating regionally integrative datasets to understand groundwater insecurities in the Colorado River Basin”

Akshay Mehra, Project Lead

Assistant Professor, University of Washington Earth & Space Sciences

Dr. Akshay Mehra (he/him) is an assistant professor in the Department of Earth and Space Sciences at the University of Washington. His lab leverages quantitative and computational methods to better understand the evolution of life and environment on Earth. Before starting at UW, Dr. Mehra held a Neukom Postdoctoral Fellowship at Dartmouth College. Prior to graduate school at Princeton University, he was a researcher at Situ Studio, where he primarily worked on projects involving human rights violations. Dr. Mehra strongly believes that scientists should apply their technical and subject matter expertise to pressing social and humanitarian issues.

Sameer Shah, Project Lead

Assistant Professor, University of Washington Environmental & Forest Sciences

Professor Sameer H. Shah (he / him) is an environmental social scientist with expertise in the human dimensions of climate change vulnerability. He is an Assistant Professor of Climate Adaptation in the School of Environmental & Forest Sciences at the University of Washington and holds the John C. Garcia Professorship. Dr. Shah’s research aims to understand the socio-economic and political processes by which climate change unevenly impacts people, and their water, food, and energy resources. He is especially interested in analyzing the equity, justice, and sustainability outcomes of climate adaptation and disaster response at multiple scales. Ultimately, Dr. Shah seeks to both inform adaptation planning that reduces the disproportionately larger climate risks experienced by marginalized groups, and to shape long-term policy strategies that transform the underlying systems responsible for exacerbating climate impacts. Dr. Shah directs the WATERS Collaborative (Water, Adaptation & Transformation: Equity, Resilience and Sustainability).

Vaughn Iverson, Data Scientist

eScience Institute, University of Washington

Vaughn looks forward to participating in the DSSG program each summer. Collaborating with the fellows, project leads and UW colleagues on challenging and impactful projects, and having a lot of fun while doing it, is a uniquely enjoyable and rewarding benefit of being affiliated with the UW eScience community.

Yuanning (Violet) Huang, University of Chicago

Violet is currently pursuing her Master’s in Computational Social Science at the University of Chicago. She uses modern techniques to examine social science issues. Her current research is centered on the causal effects of 2022’s abortion-related ballot measures on midterm election outcomes. Violet is keenly interested in the nexus of data, technology, and society and has a strong commitment to advancing public interests through the power of data. Prior to her Master’s, Violet studied Mathematics and Sociology at New York University, where her undergraduate thesis explored the spatial and temporal constraints faced by female Uber drivers.

Kimberly Kreiss, Princeton University

Kim majored in economics and minored in mathematics and English at Rutgers University-New Brunswick. She previously worked as a research assistant and then a data scientist in the Federal Reserve Board’s Division of Consumer and Community Affairs. At Princeton, she is concentrating in Economics and Public Policy and pursuing a certificate in Statistics and Machine Learning. She is currently a Graduate Fellow with the Data Driven Social Science Initiative where she provides technical expertise to researchers in the social sciences at Princeton and organizes DDSS events.

Maia Powell, University of California, Merced

Maia Powell is a Ph.D. candidate in the Applied Mathematics department at the University of California, Merced. Under the advisement of Professor Arnold Kim, work toward her thesis involves studying the nature of online disagreement and structural differences between different types of speech, as well as the spread of misinformation online. Equity has been a driving force, motivation, and goal throughout her life, and is thus present in both the interests of her personal life and her graduate research.

Aanchal Setia, University of Massachusetts Amherst

Aanchal is a second-year social psychology doctoral student with a passion for exploring the intersection of data science and psychology. Her research focuses on the impact of social inequality on the development of gender identity in individuals. She seeks to unravel the intricate relationship between societal factors and personal experiences. DSSG will enable her to cultivate an interdisciplinary lens through which she can approach her research, as well as sharpen her data science skills and benefit from invaluable mentorship provided by experts in the field.