DIoDS Conference

Nathan Alexander, PhD, is an assistant professor of curriculum and instruction in the Howard University School of Education and the Center for Applied Data Science and Analytics (CADSA). His research focuses on the history and development of quantitative and mathematical literacy, and he examines the role of context in probability theory, statistical data analysis, and mathematical education. He is the founder and director of the Quantitative Histories Workshop, a computational curriculum collective and community-centered teaching and learning lab. His research and writing have appeared in the Journal of Humanistic Mathematics, Notices of the American Mathematical Society, and PRIMUS: Problems, Resources, and Issues in Mathematics Undergraduate Studies. His work is inspired by the legacy of the great, late Bob Moses — civil rights and mathematics literacy activist, and founder of the Algebra Project.

Dr. Joseph Robertson is a citizen and enrolled member of the Sisseton Wahpeton Oyate of the Lake Traverse Reservation and is the founder and Chief Data Scientist of Mato Ohitika Analytics LLC. Dr. Robertson’s commitment to speak with students, faculty, community members, and grass roots organizations about his work is part of Mato Ohitika Analytics LLC’s broader educational and citizen science initiatives to bring the Indigenous Perspective Praxis’s holistic data science workflow designs to underrepresented communities and to provide equitable access through building academic, cultural, and community partnerships.

Dr. Robertson is currently an adjunct professor of statistics and holds a PhD in Computational Science and Statistics and a Master of Science in Statistics from South Dakota State University, and a Bachelor of Science in Mathematics from Colorado State University.

David Uminsky joined the University of Chicago in September 2020 and is currently a Research Professor 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, data science for social impact, 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.