He He

He He is an Associate Professor of Computer Science and Data Science at New York University. He is affiliated with the CILVR Lab, the Machine Learning for Language Group, and the Alignment Research Group. His research interests include understanding large language models, evaluating their outputs, and exploring human-AI collaboration. He is particularly interested in how large language models work and the potential risks associated with this technology. He is also focused on how to make humans valuable in an increasingly automated world. He is looking for 1–2 PhD students this cycle and encourages prospective students to apply to the PhD program in Computer Science or Data Science and mention his name in their application.

He He is a researcher at New York University with expertise in Machine Learning and Natural Language Processing. His work focuses on advancing question answering systems, sentiment and style transfer, and the evaluation of abstractive summarization. He has contributed to the development of frameworks like FEQA and QuAC, which assess faithfulness and context understanding in language models. His research also explores the alignment and safety of large language models, as well as the use of language models in reasoning and reinforcement learning. He has published on topics such as iterative reasoning preference optimization and the impact of language models on content diversity.