The 2019 Data Science for Social Good project teams.

The 2019 Data Science for Social Good project teams.

ADUniverse: Evaluating the Feasibility of (Affordable) Accessory Dwelling Units in Seattle

 

Emily A. Finchum-Mason, Fellow

Ph.D. Candidate, Daniel J. Evans School of Public Policy & Governance
University of Washington

Emily Finchum-Mason is a predoctoral research associate and instructor at the Daniel J. Evans School of Public Policy & Governance in Seattle. Her research interests center on the variety of roles that nonprofit organizations play in modern society, from providing social and human service to promoting civic engagement. She is also deeply invested in advancing quantitative methods in public administration and nonprofit research. Emily began her Ph.D. in Public Policy and Management at the University of Washington in 2015 and is currently working on a dissertation entitled, “The Least Among Us: Beneficiary Representation in the Modern Social Safety Net.”

Prior to joining the program, Emily spent considerable time working in both the public and nonprofit sectors. She worked as Research Associate for the Spirit of Harmony Foundation, designing advocacy campaigns to assist in the implementation of music education programs in underserved schools. She also served as a high school science teacher, and as a Research Team Coordinator for Civic Lab Chicago. Emily holds an M.S. in Public Policy & Management from the University of Washington, an M.S. in Leadership and Policy Studies from DePaul University, and a M.A. in Teaching from National Louis University. She earned a B.S. in Biological Sciences and B.A. in Psychology from the University of Illinois, Chicago.

Yuanhao Niu, Fellow

Ph.D. Student, Department of Economics
University of Notre Dame

Yuanhao Niu is a Ph.D. student at the University of Notre Dame where he pursues a doctoral degree in Economics with a minor in Computer Science. Prior to the program, he graduated with a B.A. in Economics from the Beijing Language and Culture University in 2014. He then attended the University of Illinois and the University of Sao Paulo (Brazil) for a Master’s degree in Policy Economics. He is interested in understanding the housing market, firm dynamics, and macroeconomics in the digital era. Both alternative data and machine learning methods contribute to answering the research questions. Outside of work, he spends time on standup comedy and triathlon.

Adrian Mikelangelo Tullock, Fellow

Masters Student, Interdisciplinary Data Science
University of Washington

Adrian is a master’s candidate in University of Washington’s Interdisciplinary Data Science program. He is also a core member of the Seattle branch of Women in Data Science, an organization formed to educate and inspire data scientists and support women in the field. As a member of the program’s third cohort, he is on track to graduate in 2020.

As an undergraduate, Adrian double majored in computer science and applied mathematics at Texas State University in San Marcos. During that time, he would meet mentor and friend Jesse Silva, M.A. who would inspire him towards leadership and service. Under his wing, Adrian would go on to co-coordinate numerous leadership and diversity conferences, assume student organizational and government leadership roles, and become a mentor for attending and prospective underrepresented minorities on campus. He would also perform research and study under Dr. Bahram Asiabanpour in robotics, Dr. Oleg Komogortsev in eye-tracking, and Master Dan Baker in martial arts.

Leading up to his data science master’s candidacy, Adrian worked over five years in software development, was inducted into Beta Gamma Sigma and Phi Kappa Phi honor societies as an MBA candidate, and co-authored a financial literacy book with Wilfred Brown, MBA. Having taken interest with DSSG prior to becoming a master’s candidate, he avidly approaches the opportunity with high aspirations and hopes it will advise a large scale civil or social project he looks to lead in the future.

Anagha Uppal, Fellow

Doctoral Student, Department of Geography
University of California, Santa Barbara

Anagha Uppal is a second-year graduate student in the Department of Geography at University of California Santa Barbara. Interested in computational social science, effective altruism and participatory development ideologies, she aims to adopt technology in the development of community-based solutions to local issues. Her concentrations are the food justice movement – reduction of food waste, the consumption of better food and the addressing of food insecurity, and affordable housing, residential choices and patterns and homelessness.

She has served as the training director for the local non-profit organization East Tennessee Peace & Justice Center, where she was involved with the management of Collectives and the broader sustainability of the nonprofit as a whole. She also led a few campus food justice campaigns and has participated in Clinton Global Initiative University. Currently, her work focuses on geospatial analyses of social phenomena, particularly of a cross-cultural variety. Anagha was born and raised in north India and considers it her home.

Rick Mohler, Project Lead

Associate Professor, Department of Architecture
University of Washington

Rick Mohler is a licensed architect and Associate Professor of Architecture at the University of Washington. His research focus is the nexus of land use, housing, transportation and the public realm. He is the co-chair of the American Institute of Architects Seattle Public Policy Board and a member of the Seattle Planning Commission.

Current projects are focused on advancing housing affordability at multiple scales. As a member of Seattle’s Accessory Dwelling Unit (ADU) Working Group, he is exploring both the increased production of ADU’s and their use as an affordable housing strategy. As a member of the Seattle Planning Commission, Rick is a co-author of “Neighborhoods for All – Expanding Housing Opportunities in Seattle’s Single Family Zones”. As a member of Sound Communities, a volunteer group from the academic, public, private and non-profit sectors, Rick is exploring the feasibility of establishing a regional entity to ensure that our region leverages its $60B transit investment to address housing affordability.

Nick Welch, Project Lead

Senior Planner, Seattle Office of Planning and Community Development
City of Seattle

Nick is a senior planner at the Seattle Office of Planning and Community Development. Nick focuses on residential development policy, long-range planning, and strategies to address displacement and expand opportunity. He currently leads the department’s work to promote accessory dwelling units as a strategy for infill housing, affordability, and stability. Recently, he helped shape Seattle’s landmark Mandatory Housing Affordability inclusionary rezone.

Previously, Nick was instrumental in bringing a focus on racial and social equity into the Seattle 2035 Comprehensive Plan by developing the Growth and Equity Analysis. Nick has a master’s degree in Urban and Environmental Policy and Planning from Tufts University, where he also graduated summa cum laude in International Relations and Spanish. He is a competitive distance runner and lives in Seattle with his wife and dogs.

Joseph Hellerstein, Data Science Lead

Senior Data Science Fellow, eScience Data Scientist, Affiliate Professor of Computer Science and Engineering
University of Washington

Joseph L. Hellerstein is a senior data science fellow and research scientist at the UW eScience Institute. He is an affiliate professor of Computer Science and Engineering, and is a member of the University of Washington Graduate Faculty.

His major projects focus on the analysis of biological systems such as: predicting the phenotypes of microbe communities and improving the scale and robustness of model building in biology by incorporating technologies used in software engineering (e.g., kinetics models with templates). He has developed and taught several courses: “Molecular Biology for Computer Scientists,” “Software Development for Data Scientists,” and “Computational Systems Biology for BioMedical Applications.” His primary collaborators are in Chemical Engineering, BioEngineering, and Civil Engineering.

Dr. Hellerstein was previously a software engineering manager with Google Inc. in Seattle, a principal architect at Microsoft in Redmond, WA, and a senior manager at the IBM Thomas J. Watson Research Center in Hawthorne, New York. Dr. Hellerstein received the Ph.D. in computer science from the University of California at Los Angeles. He has published approximately 200 peer-reviewed articles and two books and has taught at Columbia University and the University of Washington. Dr. Hellerstein is a fellow of the Institute of Electrical and Electronics Engineers.

 

Developing an Algorithmic Equity Toolkit with Government, Advocates, and Community Partners

 

Corinne Bintz, Fellow

Undergraduate Student, Department of Computer Science
Middlebury College

Corinne Bintz is an undergraduate student at Middlebury College, majoring in Computer Science and minoring in Global Health. Corinne is interested in using data science and other computational tools for social good, specifically for public and global health purposes. Prior to the University of Washington Data Science for Social Good program, Corinne worked as a software engineer intern for myStrength, a digital behavioral health company in Denver, Colorado where she contributed to mobile and backend development.

Corinne has experience in machine learning and data visualization. She has worked with various nonprofit organizations dedicated to social justice, such as the YWCA and Girls Who Code. Corinne spent the past spring semester in Stockholm, Sweden studying public health in the Swedish and European context. In her free time, Corinne enjoys spending time with friends outdoors in the Pacific Northwest, including hiking, backpacking, climbing, swimming and running.

Vivian Guetler, Fellow

Doctoral Student, Department of Sociology & Anthropology
West Virginia University

Vivian is a fourth year Ph.D. student in sociology at West Virginia University. As an aspiring computational sociologist and data scientist, Vivian’s research has focused on the integration of technology, computational social sciences and data science through a sociological lens. Her research interests include cyberterrorism, impact of technologies on society, ethical considerations of machine learning algorithms on society, social interactions and network structures.

Her current research analyzes how terrorist groups use technologies and the role of hacktivists in countering terrorist’s social media accounts and websites. In addition, she studies algorithm biases and how they are used in the criminal justice system. Vivian studies these phenomena using qualitative and quantitative methods, network science, natural language processing, machine learning, and exploratory visualization techniques. She has presented her research in annual conferences such as the American Society of Criminology, American Sociological Association, Media Sociology Pre-Conference, Society for Terrorism Research, T2 Conference on Technology and the Future of Terror and Network Science (NetSci).

She is excited for the DSSG opportunity and to be working alongside an interdisciplinary team to help solve society’s problems through data science.

Daniella Raz, Fellow

Master’s Student, School of Information
University of Michigan

Daniella Raz is a master’s student at the University of Michigan’s School of Information. She holds a bachelor’s degree from the University of Michigan in Political Science and Arabic and Islamic Studies, as well as a minor in Applied Statistics. During her undergraduate studies, Daniella interned at a human rights NGO in Jerusalem, and conducted research for the Rabat Social Studies Institute in Morocco and for the Arab Barometer Project. Using public opinion data collected by Arab Barometer, Daniella wrote her bachelor’s thesis on attitudes toward gender equality in Arab Muslim societies.

Prior to starting graduate school, she interned at Google in Dublin, Ireland. There, she worked with large-scale datasets on several projects, including user experience analysis and ad optimization. At the DSSG program, Daniella is looking forward to combining her previous experiences in policy and data analysis with more recent interests in digital privacy and ethical issues arising from the implementation of artificial intelligence systems.

Aaron Tam, Fellow

Master’s Student, Evan’s School of Public Policy and Governance
University of Washington

Aaron Tam is currently a master’s student at the Evan’s School of Public Policy and Governance. Aaron received a B.S. in Environmental Science and Resource Management: Wildlife Conservation and a B.A. in Political Science from the University of Washington. Aaron is an artist, activist, scientist, leader, and educator, and he has strong interests in environmental, socioeconomic, and racial justice issues.

Prior to graduate school, Aaron worked as an organizer for the Endangered Species Coalition working with native tribes, farmers, businesses, scientists, and activists to protect southern resident orcas, gray wolves, and the Endangered Species Act. Aaron also worked as a coordinator for Carbon Washington to advocate for Washington state’s first carbon tax initiative (Initiative 732). Aaron now serves as a board member for Carbon Washington helping develop and inform climate policies in Washington state.

During his free time, Aaron enjoys playing racket sports, hiking, powerlifting, and volunteering.

Mike Katell, Project Lead

Ph.D. Candidate, Information School
University of Washington

Mike Katell (he/him) is a Ph.D. Candidate at the UW Information School. His research focus is information policy, law, and ethics. Prior to his Ph.D. study, Mike worked as a technologist supporting and advising organizations working for social justice. His current research focus is algorithmic profiling and decision-making and their implications for vulnerable populations and the distribution social power. Mike is a member of the Critical Platform Studies Group and is affiliated with the Tech Policy Lab and the Value Sensitive Design Lab.

Peaks Krafft, Faculty Advisor

Senior Research Fellow
Oxford Internet Institute

Dr. Krafft is a senior research fellow at the Oxford Internet Institute in the University of Oxford’s Social Science Division. Dr. Krafft’s research, teaching, and organizing aim to bridge computing, the social sciences, and public interest sector work towards the goals of social responsibility and social justice. Dr. Krafft pursues multiple programs toward this end, including basic social science research, policy-facing computer science research, and cross-sector organizing.

Meg Young, Community Engagement Lead

Ph.D. Candidate, Information School
University of Washington

Meg is the community engagement lead for the Algorithmic Equity Toolkit. She is a Ph.D. Candidate in the Information School at the University of Washington in Seattle, where she conducts ethnographic and policy research on accountability in data-intensive systems. In the Tech Policy Lab, she has worked with government employees, community stakeholders, and tech activists on data governance and inclusive policy. She is also a co-director of the Critical Platform Studies Group, a research collective pursuing participatory action research with advocacy organizations. She holds an M.S. in Information Science and a B.A. in Cultural Anthropology from the University of Michigan. You can reach her on Twitter at @megyoung0.

Bernease Herman, Data Science Lead

Data Science Fellow, Research Staff, eScience Institute
University of Washington

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 B.S. in Mathematics and Statistics from the University of Michigan.

 

Understanding Congestion Pricing, Travel Behavior, and Price Sensitivity

 

Shirley Leung, Fellow

Doctoral Student, School of Oceanography
University of Washington

Shirley Leung is a Ph.D. candidate in the School of Oceanography at the University of Washington. Her research focuses on understanding how climate variability and change affect ocean biogeochemistry, ecosystems, and fisheries. During her time as a Ph.D. student, she has also worked as a hydrologist at the United States Geological Survey, and as a consultant at SELCO Foundation, an NGO seeking to improve housing conditions in India.

She holds a B.A. in Earth Science and Biology and a M.S. in Hydrogeology from the University of Pennsylvania. Outside of work, Shirley volunteers with the Seattle Aquarium and leads local habitat restoration events as an EarthCorps Puget Sound Steward.

Cory McCartan, Fellow

Doctoral Student, Department of Statistics
Harvard University

Cory McCartan will soon be a first-year graduate student at Harvard University, pursuing a Ph.D. in statistics. He is interested in Bayesian statistics, causal inference and applications of statistics to public policy issues, especially in the areas of economic policy, voting rights, and transportation and urban planning. Cory has previously worked in organized labor, at the Fred Hutchinson Cancer Research Center’s Department of Biostatistics, and on the Chapel Development Team at Cray, Inc. He holds a B.A. in Mathematics from Grinnell College.

CJ Robinson, Fellow

Undergraduate Student, Department of Economics and Department of Political Science
University of Washington

CJ Robinson is an undergraduate student studying economics and political science at the University of Washington. He holds strong interests in urbanization and transportation policy. CJ is currently a fellow at the Center for American Politics and Policy where he completed his undergraduate thesis focusing on public transportation and employment mobility for low-income workers. Before participating in the Data Science for Social Good program, he worked as a research assistant in the Evan’s School of Public Policy’s Social Policy & Identity Research Lab, aiding in policy and diversity research. He is excited to continue to use quantitative methods in a cooperative environment and to explore problems in urban areas like Seattle through Data Science for Social Good.

Kiana Roshan Zamir, Fellow

Doctoral Student, Operations Research / Transportation Engineering
University of Maryland

Kiana Roshan Zamir is a Ph.D. candidate in the Civil and Environmental Engineering Department at the University of Maryland specializing in Operations Research and Transportation Engineering. Her research interests are operations research, optimization, transportation network modeling, and applications of machine learning in transportation. During her graduate studies at the University of Maryland, she has worked on a range of topics including analysis of dockless bike-share and scooter-share systems, balancing bike-sharing systems, locating charging stations for electric vehicles, evaluating transit-oriented developments, school bus optimization, and validation and quality control of probe data.

Mark Hallenbeck, Project Lead

Director, Washington State Transportation Center
University of Washington

Mark Hallenbeck is the Director of the Washington State Transportation Center (TRAC) at the University of Washington. Mark has been with TRAC for over 34 years. He teaches a variety of transportation courses in Civil Engineering at the UW. Much of Mark’s research involves the collection, use, summarization, and reporting of data that describe transportation system use and performance.

He is currently working with multiple agencies in the region to examine how big data and new technology can be used to improve regional mobility, while examining how changing mobility options are affecting land use decisions. He is working on transportation data projects ranging from the analysis of the performance of dynamic tolling on I-405, to the use of electronic transit fare card and dockless bike data for better multi-modal planning.

Vaughn Iverson, Data Science Lead

Research Scientist, eScience Institute
University of Washington

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 the 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 Ph.D. in Biological Oceanography from the University of Washington in 2015, and also holds an M.S. in Computer Science from the University of Washington, Seattle, and a B.S. in Computer Science and Chemistry from Washington State University, Pullman. Prior to commencing his Ph.D. 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 U.S. patents.

 

 

Natural Language Processing for Peer Support in Online Mental Health Communities

 

Shweta Chopra, Fellow

Master’s Student, Social Policy and Data Analytics
University of Pennsylvania

Shweta Chopra is a graduate student in Social Policy and Data Analytics at the University of Pennsylvania’s School of Social Policy and Practice. Her interests lie in the practical application of data science techniques to real-world problems of social significance. Shweta brings together an interdisciplinary background in economics, liberal arts, policy and data science and hopes to offer an ethical, inclusive, and compassionate approach to her work.

Shweta has three years of experience encompassing consulting and analytics assignments. She worked with the Indian government at both the central and state levels, with technological and data interventions forming a core pillar of her work. Her work with the Ministry of Housing and Urban Affairs focused on research into global implementations of Information and Communications Technology interventions for citizen safety. She then worked as a consultant with the Education Department in Himachal Pradesh, India on systemic governance interventions to improve student learning outcomes in the state.

Shweta completed her Bachelor’s degree in Economics from Delhi University, and the Young India Fellowship in Liberal Studies from Ashoka University, before earning her Master’s at Penn. Moving forward, she hopes to support governments and non-profits with leveraging data science on their path to greater social justice.

David Nathan Lang, Fellow

Doctoral Candidate, Graduate School of Education
Stanford University

David is a doctoral student in the Economics of Education program and an Institute of Education Sciences Fellow. He graduated from UCLA in 2008 with a B.A. in Economics and a B.S. in Actuarial Mathematics. Prior to his doctoral studies, David worked for five years as a research analyst at the Federal Reserve Bank of San Francisco.

His research interests include causal inference, psychometrics, and “text as data” methods in education research. His dissertation focuses on platform design in educational contexts. Specifically, David’s research focuses on how learning platforms can augment instructors’ abilities to anticipate student needs. At Stanford, David also obtained a master’s degree in Management Science and Engineering. He is concurrently working on a master’s degree in Computer Science. You may reach him at dnlang86(at)stanford.edu.

Kelly McMeekin, Fellow

Student, Database Management
South Puget Sound Community College

Originally educated in English and Urban Education and Multiculturalism, Kelly has worked in the healthcare, finance, government, logistics, fashion, and education sectors. Across industries, her work has been dominated by her interest in using data analysis to craft innovative solutions and process improvements. In 2018, Kelly embarked on an official career pivot and enrolled in statistics and database management courses at South Puget Sound Community College, where she discovered a wholly unexpected affection for programming in C# and SQL.

Kelly holds a BA from Santa Clara University. Notable past achievements include: doubling profits for a medical practice ten months after assuming operational control; developing an emergency supplies vendor registration form that was later adopted by counties across California; and creating, at age twelve, her data-obsessed pièce de résistance: an eighty-page encyclopedia of all things Harry Potter.

Tim Althoff, Project Lead

Assistant Professor, Computer Science & Engineering
University of Washington

Tim Althoff is an assistant professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. His research advances computational methods to improve human well-being, combining techniques from data mining, social network analysis, and natural language processing.

Tim holds Ph.D. and M.S. degrees from the Computer Science Department at Stanford University, where he worked with Jure Leskovec. Prior to receiving his Ph.D., Tim obtained M.S. and B.S. degrees from the University of Kaiserslautern, Germany. He has received several fellowships and awards including the SAP Stanford Graduate Fellowship, Fulbright scholarship, German Academic Exchange Service scholarship, the German National Merit Foundation scholarship, and a Best Paper Award by the International Medical Informatics Association. Tim’s research has been covered internationally by news outlets including BBC, CNN, The Economist, The Wall Street Journal, and The New York Times.

Dave Atkins, Project Lead

Research Professor, Psychiatry and Behavioral Sciences
University of Washington

Dave Atkins, Ph.D., is a research professor of Psychiatry and Behavioral Sciences at the University of Washington, where he co-directs the Behavioral Research in Technology and Engineering (BRiTE) Center focused on technology and mental health. He leads an interdisciplinary research team including engineers, computer scientists, designers, and clinical researchers who develop spoken language technologies to estimate quality metrics in counseling, and how such technologies can assist training, supervision, and quality assurance of evidence-based counseling services. In addition to his academic work, Dr. Atkins is a co-founder of a start-up, Lyssn.io, that is focused on developing and implementing technology to support evidence-based counseling.

Valentina Staneva, Data Science Lead

Senior Data Scientist, eScience Institute
University of Washington

Valentina Staneva started as a data scientist at the eScience Institute in March, 2015. Prior to joining the University of Washington, she was a Ph.D. student in the Applied Mathematics & Statistics Department at Johns Hopkins University. Her research was with the Center for Imaging Science and was devoted to developing methods for tracking deforming objects in videos and statistical estimation of their dynamics.

Valentina has a Bachelors degree in Mathematics from Concord University and between her undergraduate and graduate studies she spent 1.5 years working at Los Alamos National Laboratory on problems in imaging, optimization and compressed sensing. She has broad interests in extracting information from different types of data and building tools for its use.