Tosif Ahamed

Contact: ahamedt at janelia dott hhmi dot org

I am currently a Theory Fellow at HHMI's Janelia Research Campus and will be joining the Department of Bioengineering at the Indian Institute of Science and Technology, Bangalore in August 2026.


How do populations of neurons coordinate their activity to give rise to behavior? How do gene regulatory networks govern how an entire organism develops? How does the brain coordinate with the body during sickness and other changes in physiological state? These questions sit at the frontier of quantitative biology. Recent technological advances now make it possible to measure these systems in quantitative detail, at high spatial and temporal resolution. My research focuses on the inverse problem at the heart of modern biology: given high-dimensional measurements of a living system, how do we infer the underlying dynamical principles? I develop mathematical and computational tools, drawing on dynamical systems theory, operator-theoretic methods, and machine learning, to make this inference tractable.

The specific problems I work on include how populations of neurons encode and process complex, unpredictable sensory stimuli to coordinate behavior; how brain and body reorganize during sickness, using large-scale neural recordings as a window into this process; and how gene expression landscapes evolve across space and time during embryonic development, inferred from single-cell RNA sequencing and cell-tracking data in C. elegans embryos.

Research

Full list of my publications is available on Google Scholar

Behavioral dynamics from data

(With Antonio Costa and Greg Stephens) Dynamical systems analysis of C. elegans locomotion revealed that the dynamics could be captured by a 7-dimensional attractor. Study of the spectrum of Lyapunov exponents showed an intriguing mathematical structure, where behavioral variability shows signs of chaotic dynamics with a damped-driven Hamiltonian structure.

Link to the preprint
Link to the paper on Nature Physics
Nature Physics News and Views Feature
F1000 Recommendation
Link to Twitter thread

Extrasynaptic signaling enables an asymmetric juvenile motor circuit to produce a symmetric gait

(With Yangning Lu and Zhen Lab) The first-stage larval C. elegans worm has an unusually asymmetric motor circuit, where muscles on only one side receive direct excitation from motor neurons. Using electron microscopy, calcium imaging, genetic perturbation, optogenetics, and computational modeling, we showed that extrasynaptic volume transmission provides the excitation necessary for muscle contraction on the other side.

Link to the preprint
Link to Twitter thread

Maximally predictive ensemble dynamics from data

(With Antonio Costa, David Jordan and Greg Stephens) Animal behavior, like language, has structure across multiple scales. We proposed a solution using operator-theoretic methods: learning an operator representation of the dynamics to build a maximally predictive state-space and decompose hidden scales via the operator eigenvectors.

Link to the preprint
Link to Twitter thread

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