Kangwook Leeمشاهده پروفایل
دانشیار
- Large Language Models
- LLM Agents
- Deep Learning
- +۴ مورد دیگر
Kangwook Lee serves as an Associate Professor in the Electrical and Computer Engineering Department with a courtesy appointment in Computer Sciences at the University of Wisconsin-Madison, where he also holds a Discovery Fellowship. He concurrently leads deep learning research initiatives at KRAFTON, bridging academic and industry innovation in artificial intelligence. His academic foundation includes a PhD in Electrical Engineering and Computer Sciences from UC Berkeley (2016), preceded by research assistant and postdoctoral positions at KAIST's Information and Electronics Research Institute. Hailing from Seoul, South Korea, Lee maintains active research operations through his laboratory in Madison's Discovery Building. Lee's research program centers on Large Language Models and LLM agents, with rigorous theoretical and empirical investigations into their operational mechanisms and improvement pathways. His work spans in-context learning dynamics, agent-based social simulations, multi-domain reward modeling, and efficient inference techniques, emphasizing both fundamental understanding and practical enhancement of AI capabilities. Recent publications reveal a concentrated effort on overcoming length generalization barriers, enabling compositional reasoning with rare concepts, and developing robust feature selection frameworks. His 2025 publications demonstrate significant advancements across LLM architecture, evaluation methodologies, and application domains. Key trends include the emergence of task vector representations in in-context learning, development of superposition techniques for multi-task processing, and innovative approaches to speculative decoding for multimodal systems. These works collectively advance the field toward more efficient, generalizable, and interpretable language models. Lee's research excellence is recognized through prestigious accolades: NSF CAREER Award (premier early-career grant) IEEE Joint Communications Society/Information Theory Society Paper Award Amazon Research Award KSEA Young Investigator Grant Award As principal investigator of the Lee Lab, he directs a dynamic research group focused on cutting-edge AI challenges. His work integrates theoretical analysis with empirical validation to address fundamental limitations in modern language models, while industry collaborations through KRAFTON ensure real-world impact. Current projects emphasize agent-based social dynamics modeling, efficient inference architectures, and robustness frameworks for diverse deployment scenarios.
