David Uminsky joined the University of Chicago in September 2020 as a senior research associate and Executive Director of the Data Science Institute. He was previously an associate professor of Mathematics and Executive Director of the Data Institute at the 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 and 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 to 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.
How Do We Know It’s Working? Evaluating Field-Building for Social Impact
Thursday, June 5 at 12pm UTC/ 8am EST
Field-building efforts—whether through networks, capacity strengthening, or digital public goods—are vital to advancing social impact. But how do we evaluate their effectiveness? This interactive session explores practical strategies for evaluating field-building initiatives, drawing on real-world examples from data.org and TSIC. We’ll share lessons on defining field-building impacts, measuring reach and…