Assistant Professor, Department of Physics
Committee on Computational and Applied Mathematics (CCAM)
We work on problems in quantitative biology, non-equilibrium dynamics, and theoretical computer science. A frequent question is how collective dynamics in physical and biological systems can generalize past experiences, i.e., learn, and respond differently to future inputs.
Current work includes:
1. Interactions between internal transients and external time variations
(in circadian clocks with the Rust lab, in gene regulation with the Tay lab,
in immunology with the Wang lab, in neural networks)
2. Learning in materials
(elastic materials, DNA systems, active materials).