Current Research

Data & Evaluation. Create new data engines. Create benchmarks that are formally verified. Unify scientific inverse problems into common frameworks.

Models & Architecture. Create new effective representations, such as for time series.

Inference & Search. Develop principled Bayesian inference methods using diffusion priors. Develop advanced LLM reasoning methods such as dynamic tree decomposition and self-training.