Title

Jeffrey Markowitz

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Title/Position
Assistant Professor
Areas of Research

Areas of Research

Neuroengineering
Contact

Contact

U.A. Whitaker, Office 3102Georgia Tech
jeffrey.markowitz@bme.gatech.edu
404.385.3666
MarkoLab
Education

Education

  • Ph.D. in Computational Neuroscience, 2014 - Boston University
  • B.A. in Philosophy, 2006 - Johns Hopkins University
Research Interests

Research Interests

The overall mission of my lab is to resolve how the brain controls movement in health and disease. We strongly believe that one of the primary challenges in answering this question is technical, namely that we require more precise and robust tools for measuring and quantifying both behavior and neural activity. Thus, we are pursuing the development of novel experimental and computational techniques for tracking kinematics in mice and new fluorescent biosensors for tracking neural activity. We also deploy these tools in freely moving mice to resolve the key nodes that translate intention into action, with a particular focus on the dopamine pathway, which is strongly implicated in a wide-range of neurological disorders. 

Teaching Interests

Teaching Interests

My teaching is focused on fundamentals of physiology, neuroengineering and machine learning at the undergraduate and graduate levels. Furthermore, my research is focused on student-enrichment, and actively involves both graduate and undergraduate students from a variety of disciplines.
Publications

Publications

Journal of Neuroscience
Johnsen, K. A., Cruzado, N. A., Menard, Z. C., Willats, A. A., Charles, A. S., Markowitz, J. E., & Rozell, C. J. (2026). Bridging model and experiment in systems neuroscience with Cleo: The closed-loop, Electrophysiology, and Optophysiology simulation testbed. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 46(1), e2239242025.
Science Advances
Ulutas, E. Z., Pradhan, A., Koveal, D., & Markowitz, J. E. (2025). High-resolution in vivo kinematic tracking with customized injectable fluorescent nanoparticles. Science Advances, 11(40), eadu9136.
PMLR
Ke, J., Wu, F., Wang, J., Markowitz, J., & Wu, A. (2025, June 18). Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors. Forty-Second International Conference on Machine Learning.
Current Opinion in Behavioral Sciences
Markowitz, J. E. (2025). Act natural: a review of new methods for assessing dopamine’s role in natural behavior. Current Opinion in Behavioral Sciences, 64(101532), 101532.
Dystonia
Abdal Qader, A., Donsante, Y., Markowitz, J. E., Jinnah, H. A., Pandarinath, C., & Hess, E. J. (2025). Behavioral signature of trihexyphenidyl in the TOR1A (DYT1) knockin mouse model of dystonia. Dystonia, 4(15034), 15034.
eLife
Lindsey, J., Markowitz, J. E., Gillis, W. F., Datta, S. R., & Litwin-Kumar, A. (2024). Dynamics of striatal action selection and reinforcement learning. In eLife.
Nature
Markowitz, J. E., Gillis, W. F., Jay, M., Wood, J., Harris, R. W., Cieszkowski, R., Scott, R., Brann, D., Koveal, D., Kula, T., Weinreb, C., Osman, M. A. M., Pinto, S. R., Uchida, N., Linderman, S. W., Sabatini, B. L., & Datta, S. R. (2023). Spontaneous behaviour is structured by reinforcement without explicit reward. Nature.
Neuron
Gschwind, T., Zeine, A., Raikov, I., Markowitz, J. E., Gillis, W. F., Felong, S., Isom, L. L., Datta, S. R., & Soltesz, I. (2023). Hidden behavioral fingerprints in epilepsy. Neuron.

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