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The Community Data Fellows program pairs local, community-based nonprofit organizations with UChicago graduate students who possess skills in technology and policy analysis. Through this program, we meet social impact organizations where they are on the data spectrum. Fellows work with organizations to determine how best to use data, build data capacity across program staff, and scope projects that advance the mission. By understanding the organization’s data capacity, Fellows are able to create solutions that persist and add value at the completion of the work.

The Community Data Fellows program is supported in part by the Public Interest Technology University Network (PIT-UN), an initiative of New America’s Public Interest Technology Program.


Team

David Uminsky joined the University of Chicago in September 2020 as a senior research associate and Executive Director of Data Science. He was previously an associate professor of Mathematics and Executive Director of the Data Institute at University of San Francisco (USF). His research interests are in machine learning, signal processing, pattern formation, and dynamical systems.  David is an associate editor of the Harvard Data Science Review.  He was selected in 2015 by the National Academy of Sciences as a Kavli Frontiers of Science Fellow. He is also the founding Director of the BS in Data Science at USF and served as Director of the MS in Data Science program from 2014-2019. During the summer of 2018, David served as the Director of Research for the Mathematical Science Research Institute Undergrad Program on the topic of Mathematical Data Science.

Before joining USF he was a combined NSF and UC President’s Fellow at UCLA, where he was awarded the Chancellor’s Award for outstanding postdoctoral research. He holds a Ph.D. in Mathematics from Boston University and a BS in Mathematics from Harvey Mudd College.

Mindi has experience managing, sourcing and scoping a portfolio of data science experiential learning partnerships across social impact organizations, corporate, civic and government entities. Mindi managed earlier iterations of our work with the 11th Hour Project at the University of San Francisco where she served as the Senior Director of Strategy and Operations of the Data Institute. Mindi is a member (inactive) of the California and Illinois bars and received her JD from UC Hastings and her BS, Political Science from Santa Clara University.

Susan Paykin is the Program Lead of the Open Spatial Lab at the Data Science Institute (DSI) and oversees its programmatic, research, and partner engagement activities. As Associate Director, Community-Centered Data Science, Susan also helps lead DSI’s social impact and outreach initiatives including 11th Hour Project and Capacity Accelerator Network collaborations, and oversees the Community Data Fellows program, which provides data science support for community and nonprofit organizations. She was previously the Research Manager at the Center for Spatial Data Science at UChicago and has served leadership, research, and advocacy roles for environmental and social impact organizations. She holds a Master in Public Policy (M.P.P) from the Harris School of Public Policy at University of Chicago and a B.A. in International Studies from Brandeis University.

Ari Zickau is the Community Data Fellows Program Manager at the Data Science Institute. The Community Data Fellows program provides data science support for local and global community and nonprofit organizations by connecting them with students through applied learning opportunities. Before relocating to Chicago, Ari served as the Community Experience Manager for the City of Boise, Idaho. In addition to program management work, they also have extensive experience in public and academic libraries. He holds a MS in Library and Information Science from San José State University and a BA in English from Boise State University. In the sphere of data science, Ari is interested in equitable access and practices, open data, civic engagement, and social impact.

Winter 2024 Fellows

Raúl Castellanos holds a Joint Degree in International Relations and Political Science from the Instituto Tecnológico Autónomo de México (ITAM) and is pursuing an MS in Computational Analysis and Public Policy (MSCAPP) at the University of Chicago’s Harris School of Public Policy. With professional experiences ranging from serving as the Open Data Deputy Director for the Public Agency of Digital Innovation (ADIP) in Mexico City to contributing as a Data Analyst for Powered by People, Raúl demonstrates expertise in data analysis, cost-effective strategies, and project leadership.

Contact Raúl

Jonathan Juarez is currently a second-year master’s degree student in the Computational Analysis and Public Policy (CAPP) program at the Harris School of Public Policy. After earning his B.S. in Political Science and Economics from Texas A&M University, he spent five years working as a data analyst and database engineer in Texas. Today, Jonathan is dedicated to using his expertise to address challenges faced by individuals facing discrimination, poverty, and those in marginalized communities.

Contact Jonathan

Josemaria is a research assistant for the Community Data Fellows program at the Data Science Institute. He received his bachelor’s degree in Political Science at ITAM (Mexico) and he is currently pursuing a master’s degree in Computational Analysis and Public Policy at the University of Chicago. Prior to studying at the University, he was a product manager at Mexico City’s Government (ADIP). He also worked as an analyst at IMCO, a Mexican policy think tank.

Contact Josemaria

Hieu completed his undergraduate studies in Quantitative Economics and Mathematics from Dickinson College, and he is currently pursuing a master’s degree in Computational Analysis and Public Policy at the University of Chicago. Before UChicago, Hieu worked on database engineering and program evaluation at Save the Children International in Vietnam and contributed to efficient operational and analysis workflows. His strengths include database management and data analysis.

Contact Hieu

Stephania is a second-year graduate student at the University of Chicago, where she is pursuing an MS in Computational Analysis and Public Policy. Originally from Peru, her professional journey includes valuable experience in education, gender, and transportation policy, leveraging data to inform the decision-making process. She is passionate about strengthening the data capacity of organizations, empowering them to make a positive impact on their communities.

Contact Stephania

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