Data Science for Social Good Participants – Summer 2021

Rowana Ahmed is a Master’s student in the Health Data Science program at Harvard University. She earned her BSE and MSE in Bioengineering from the University of Pennsylvania. Prior to starting her graduate program at Harvard, Rowana worked as a Technology Consultant at Accenture and later as an Analytics Manager at Humanyze, a people analytics startup dedicated to improving organizational health using social network analysis.

Rowana’s research focus is in social determinants of health, and she is particularly interested in harnessing the power of data science to design public policy aimed at improving health equity. She is excited to work with the DSSG team this summer to help curb gerrymandering practices for more just and fairer elections.

Katherine Chang is a PhD student in Education Policy, Organizations, and Leadership at the College of Education, University of Washington and an MPA student in Social Policy at the Evans School of Public Policy and Governance.

Katherine’s research agenda is composed of three strands of inquiry: the politics of education reform, the politics of race in education policymaking, and cross-systems interactions between social and education policy. Her dissertation examines the political institutions engaged in court-mandated school finance reform and interrogates the racialized geographies tied to educational funding gaps. Katherine primarily uses quantitative and computational social science methods in her research, with particular interest in social network analysis and text-as-data methods.

Katherine’s graduate studies are part of her continued journey to train in equitable data practices and responsible, justice-centered research. She is looking forward to participating in DSSG to realize data-driven solutions for mediating social inequities and to promote ambitions towards research rooted in social good.

James Lamar Foster is a Ph.D. Candidate at The University of Washington’s Education Policy, Organizations, and Leadership program in the College of Education. His work investigates questions at the intersections of race, place, policy, and practice. His current research uses analytical approaches from critical and organizational theory in concert with computational methods to understand how school leaders create conditions to foster marginalized students’ social-emotional development. Lamar has been interested in the work of DSSG fellows since arriving at the University of Washington. Their focus on computational methods and social good piqued his interest, which prompted him to apply. He is particularly excited to work on the Geography, Equity, and the Seattle $15 minimum wage ordinance project, which explicitly focuses on equity, policy, and place. In his free time, Lamar enjoys spending time with friends and family and watching Manchester United F.C.

Delaney Glass is a 3rd year Ph.D. student in Biological Anthropology at UW. As a human biologist and anthropologist, her work probes the effects of and variation in biologically measured and perceived stress among children and adolescents. She utilizes mixed methods and interdisciplinary approaches from evolutionary biology, cultural anthropology, and social epidemiology. Her current research utilizes previously collected and archived biological samples from the Chaco Area Reproductive Ecology Program to understand neuroendocrine variation across early to mid-puberty among indigenous Qom girls living in Argentina. Additionally, her proposed research in Amman, Jordan will focus on how global-local dynamics, intraindividual variation in cultural consensus, and adolescent stress interact with the timing, tempo, and hormonal variation in early to mid-adolescence. She is passionate about transparent and reproducible research and utilizing qualitative and quantitative data. In her free time, she enjoys speaking Arabic, gardening, cooking, and reading.

Chris is an incoming PhD student in Industrial and Systems Engineering at the University of Washington. Prior to returning to academia, Chris worked as a structural engineer where he primarily worked on disaster response work upon the aftermath of catastrophic events such as Hurricane Harvey, Hurricane Maria, earthquakes in Mexico/Alaska, and other similar events. This type of work has carried into working in the Disaster Data Science Lab (UW) where he developed an algorithm to estimate distance in images between pedestrians for adjudicating social distance compliance. He is excited and humbled by the prospect of working with other DSSG fellows, data scientists and project leads on the “Geography, equity, and the Seattle $15 minimum wage ordinance” project. It will present an excellent opportunity to collaborate with other subject matter experts to provide a holistic evaluation of the research project. I expect the connections and lessons learned as a DSSG fellow will influence my future work in academia as well as community engagement opportunities.

Michael Gregory Souffrant is a Ph.D. candidate in Computational Biophysical Chemistry at Georgia State University. His research is based on molecular dynamics (MD) and analyzing computer simulations of biomolecular structures. He is currently probing the impact of mutations on HIV in resisting drug inhibition. Michael is interested in learning more data visualization and machine learning techniques at the Data Science for Social Good internship. He is excited about the program’s collaborative opportunities and his contribution in using computational approaches to resolve political issues. He was the president of the Chemistry Graduation Student Association and hosted/organized the Chemistry Research Symposium. He taught environmental and physical sciences to K-12 students as a fellow of the Bio-Bus program. He enjoys working out, social dancing and playing basketball. Michael currently lives in Atlanta, Georgia.

Mahader Tamene (she/her/hers) is a PhD student in the Division of Epidemiology at UC Berkeley’s School of Public Health. A public health scholar dedicated to advancing health and justice in underserved and historically marginalized communities globally, her research focuses on maternal and child mental health disparities, particularly community-based interventions that address the structural drivers of these disparities. She envisions research that translates beyond academia to change the world around us. She believes interdisciplinary, reflective, and transformative leadership is necessary for this change.

Mahader has worked in community health education, health research, program implementation and evaluation both domestically and abroad. She holds an MSc in global health and population from Harvard T.H. Chan School of Public Health and a BA in public policy and African/African-American studies from the University of Chicago.

Noah Benson is a senior data scientist at the University of Washington’s eScience Institute. His research explores the domain of human neuroscience and vision with an emphasis on understanding the relationship between the anatomical structure of the brain and its function. Noah’s career has focused heavily on developing and teaching reproducible neuroscience computations for scientific insight, many of which are documented on his website (http://nben.net/) and GitHub pages (https://github.com/noahbenson/). At UW, Noah administers the Software Carpentry program for data science education, is a founding member of the eScience Equity Team, and co-administers the NeuroHackademy summer course (neurohackademy.org).

In addition to his research activities, Noah has a keen interest in community engagement, political activism, and human rights advocacy, and he is excited about the opportunity to leverage his data-science expertise to approach such topics through the DSSG program this summer.

Dr. DeFord is an assistant professor in the Department of Mathematics and Statistics at Washington State University. His research program focuses on applying algebraic and combinatorial methods to the analysis of social data with an emphasis on applications of discrete sampling techniques to political redistricting and social network models. Prior to joining the faculty at WSU, he completed a postdoctoral position at MIT in the Geometric Data Processing Group while collaborating with the Metric Geometry and Gerrymandering Group on mathematical modeling of political geography and developing open-source software for detecting and combating gerrymandering. Dr. DeFord completed his Ph.D. at Dartmouth College with a thesis evaluating dynamical models for complex networks. The Data Science for Social Good program provides an amazing opportunity to collaborate with a diverse and interdisciplinary team of researchers and he is looking forward to working with them on problems with immediate relevance to current redistricting efforts.

Bernease Herman is a data scientist at the University of Washington eScience Institute. Her research focuses on evaluation metrics and interpretable machine learning through the use of synthetic data and other generative techniques. She’s worked on various data science problems from data collection and analysis strategies in autonomous marine vehicles to predicting inequity in Seattle urban data. Bernease is also employed at WhyLabs, an AI observability and monitoring startup, building model and data monitoring tools using approximate statistics techniques. This summer will mark Bernease’s fifth UW Data Science for Social Good program. She is excited to apply her interests in model evaluation, data generation, and societal impact to the important issue of redistricting.

Jose Hernandez is a senior data scientist at the University of Washington’s eScience Institute. He received his BA from the University of California, Irvine in Social Ecology (2001-2006) and his Ph.D. in Educational Measurement and Statistics from the University of Washington where he studied the application of causal inference methodology in the absence of randomization on complex data structures (2010-2015).

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.

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.

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, Romich is excited to work with the DSSG summer project as a way of learning about data science techniques applicable to large-scale administrative data set. She looks forward to answering some heretofore unanswerable questions about residential mobility and poverty policy.

Valentina Staneva is a Senior Data Scientist at University of Washington’s eScience Institute. As part of her role she collaborates with researchers from a wide range of domains on extracting information from large datasets such as images and time series. She regularly teaches data science skills and best practices for reproducible research to diverse audiences. Valentina holds a Ph.D. in Applied Mathematics & Statistics from Johns Hopkins University with a focus on computer vision, and previously worked at Los Alamos National Laboratory on problems in imaging, optimization and compressed sensing.