research Information Bottleneck & Representation Learning Developing principled, information-theoretic frameworks for extracting meaningful representations from complex multimodal data. Neural Circuits & Dynamics Applying information theory and statistical physics to understand how the brain encodes, compresses, and communicates information. Physics-Tailored Machine Learning Building machine learning models that respect physical symmetries and constraints to discover new physics from experimental data. software