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My research group aims to build and improve language models. Methodologically, we study data-driven methods that combine deep-learning based models with probabilistic controls. We are interested in applications in improved scaling, efficiency, model reasoning, and long-context generation.
I study post-training of AI systems for coding and related tasks. I'm interested in improving model reasoning for long-horizon tasks. Bio From 2016–2026, I was a Professor at Harvard and then Cornell. My group's research was recognized with an NSF CAREER Award and a Sloan Fellowship. My students have won paper awards at conferences for NLP, Hardware, and Visualization, and gone on to do really neat things. From 2019–2024, I also worked as a researcher at Hugging Face and helped on early open-source LLM projects. In 2024, I helped start the Conference on Language Modeling. I have a youtube…
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