Speaker "Allison Gilmore" Details Back



The Shape of the Future: Topological Data Analysis Applied to Predictive Modeling


The combination of Topological Data Analysis and Machine Learning creates predictive models that are both more accurate and can be stood up in a fraction of the time. The talk will discuss how prediction models work within the TDA framework and why superior outcomes can be achieved.


Dr. Gilmore is currently a data scientist on the team at Ayasdi where she specializes in highly complex and dimensional data across a variety of industries. Prior to joining Ayasdi, Allison served as a National Science Foundation Post-Doctoral Fellow and an Assistant Adjunct Professor in mathematics at the University of California Los Angeles. Dr. Gilmore also did post-doctoral research at Princeton University. She received her Ph.D. in mathematics from Columbia University in New York in May 2011. Allison completed her undergraduate and masters degrees from Washington University where she was selected as as a Rhodes Scholar. She studied at Green College, Oxford University, and graduated in 2006 with an M.Phil. (with distinction) in sociology. Her research interests include topology and geometry, network analysis and social movements. Dr. Gilmore serves on the board of The Friends of the Mandela Rhodes Foundation whose mission is to fund the development of exceptional leadership capacity in southern Africa.