Computation, AI & Theory-Driven Biophysics (CATBio 🐱🧬 )

Our group combines theoretical biophysics, multi-scale computation, and artificial intelligence to explore a wide spectrum of biological phenomena. This multidisciplinary approach equips students with valuable computational, analytical, and organizational skills—highly sought after in both academia and industry. Our current research efforts focus on four main directions:

I. Developing AI- and physics-based methods to predict allosteric communication in biomolecular molecular assemblies;
II. Uncovering sequence-encoded dynamics in biomolecular condensates using multi-scale computational models;
III. Constructing mesoscopic and systems-level models to elucidate transcriptional and epigenetic regulation of chromatin;
IV. Advancing generative and explainable AI approaches for modeling and interpreting biomolecular dynamics.