Yong Jae Lee is an Associate Professor in the Department of Computer Sciences at the University of Wisconsin-Madison. His research interests are in computer vision and machine learning, with a focus on robust visual recognition systems that learn to understand the visual world with minimal human supervision. Before joining UW-Madison in 2021, he spent one year as an AI Visiting Faculty at Cruise and six years as an Assistant and then Associate Professor at UC Davis. He received his PhD from the University of Texas at Austin in 2012 and was a postdoc at Carnegie Mellon University (2012-2013) and UC Berkeley (2013-2014).

Professor Lee is co-author of the widely cited paper “Visual Instruction Tuning,” which proposes LLaVA (large language and vision assistant), an end-to-end trained large multimodal model that connects a vision encoder and an LLM for general-purpose visual and language understanding. He is also co-author of “Segment Everything Everywhere All at Once,” which proposes a novel decoding mechanism enabling diverse prompting for all types of segmentation tasks.

Professor Lee is a recipient of the ARO Young Investigator Program Award (2017), UC Davis Hellman Fellowship (2017), NSF CAREER Award (2018), AWS Machine Learning Research Award (2018 and 2019), Adobe Data Science Research Award (2019 and 2022), UC Davis College of Engineering Outstanding Junior Faculty Award (2019), Sony Focused Research Award (2020 and 2023) and UW-Madison SACM Student Choice Professor of the Year Award (2022). He and his collaborators received the Most Innovative Award at the COCO Object Detection Challenge, ICCV 2019 and the Best Paper Award at BMVC 2020.