Research Themes
Modeling & Inference. We develop models that learn useful structure from complex data, from representation learning to new architectures to inverse problems.
Reasoning & Self-Improvement. We study how models solve hard problems by searching, checking their work, and improving from feedback, including code generation, LLM search, and programmable agents.
Scientific Discovery. We use agents, foundation models, and closed-loop experiment design to advance discovery in biomedical imaging, neural data, protein engineering, and more.