Research Scientist at Basis Research Institute, New York City. Previously faculty at Tel Aviv University and postdoc at MIT. I study what can and cannot be recovered from noisy, incomplete data — through the lens of inverse problems, super-resolution theory, dynamical systems, and scientific machine learning.
Contact: dima.batenkov@gmail.com
News
🎉Oct 20262 papers accepted at NeurIPS 2026! "Wasserstein Residuals: Learning Gradient Flows from Population Dynamics" with Markus Heinonen, Yair Shenfeld, Ricardo Baptista, Dan Waxman, Tim Cooijmans, and Eli Bingham (main conference, poster), and "A Continuous-Discrete Switching Dynamical Model for Multi-Agent Interactions" with Anushri Arora, Ralph Peterson, Emily Mackevicius, Dan Waxman, and Matt Levine (Workshop on AI for Stochastic Dynamics).
