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Dmitry Batenkov

People

Dmitry Batenkov

Research Scientist, Basis Research Institute

Dmitry Batenkov is a research scientist at Basis, working on probabilistic inference, scientific machine learning, and the mathematical foundations of inverse problems in imaging and dynamical systems. He was previously a tenure-track assistant professor of applied mathematics at Tel Aviv University, a visiting scholar at the Courant Institute, and a postdoctoral associate at MIT.

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Education

  • PhD, Mathematics
    Weizmann Institute of Science, 2014
  • BA, Computer Science
    Technion, 2002

Previous Appointments

  • Visiting Scholar
    Courant Institute, NYU
  • Assistant Professor of Applied Mathematics
    Tel Aviv University
  • Postdoctoral Associate
    MIT
  • Postdoctoral Researcher
    Technion

About

I am a research scientist at Basis, where I work on probabilistic inference, scientific machine learning, and the mathematical foundations of inverse problems. My research connects ideas from harmonic analysis, inverse problems, and modern machine learning, with applications across imaging, dynamical systems, and the quantitative study of animal behavior.

Recent threads of my work include the theory of mathematical super-resolution — how accurately one can recover sub-Rayleigh features from bandlimited noisy data, and which algorithms achieve the fundamental limits; identification of reaction-diffusion systems and inverse problems for parabolic PDEs via exponential fitting; physics-informed deep learning for acoustic source localization and atmospheric radiative transfer; counterfactual semantics for hybrid dynamical systems; and computational urban ecology of free-ranging rats and other animals.

Before joining Basis I was a tenure-track assistant professor of applied mathematics at Tel Aviv University and a visiting scholar at the Courant Institute, NYU. Earlier I was a postdoctoral associate at MIT with Laurent Demanet and a postdoctoral researcher at the Technion with Michael Elad. I completed my PhD in mathematics at the Weizmann Institute of Science, supervised by Yosef Yomdin.

Projects

Current and recent Basis projects.

Collaborative Intelligent Systems

Multimodal sensing and modeling tools for studying social behavior in real-world animal groups: inferring social values/preferences, and how environments shape cognition, coordination, and affect.

Core Technology

Foundational methods for reasoning, probabilistic inference, and recovery from indirect measurements in complex systems.

Collaborations

Ways to work with Dmitry at Basis.

Collaborative research projects

My favorite projects sit where a sharp mathematical question meets a real measurement problem. Areas I am actively working on include super-resolution and exponential fitting, system identification for PDEs, physics-informed inversion for atmospheric and acoustic problems, and computational analysis of animal behavior in the wild. I am always interested in new collaborators on either the theory side or the measurement side of these problems.

Co-advising postdocs and trainees

Over the past decade I have advised and co-advised a number of MSc and PhD students, postdocs, and interns in computational and applied math. I continue to enjoy working with trainees who want to pair rigorous theory with messy real-world data, and I am happy to discuss possible projects.

Software

Open-source research code and tools.

collab-environment

A shared environment representation used across the Collaborative Intelligent Systems project to model and simulate how animals and agents behave in naturalistic settings.

collab-splats

Turns multi-view field recordings into 3D Gaussian splats, meshes, and semantically annotated scenes that feed downstream behavioral and ecological analyses.

RTPINN

A mesh-free physics-informed neural network solver for the radiative transfer equation.

Recent Publications

Recent papers and preprints.

Selected Publications

Earlier selected work.