Active Generative Agents Lab
Active Generative Agents Lab
We are hiring undergrad researchers and PhD students!
Please see Recruiting.
Intelligent biological agents generate actions to explore the world actively. Artificially intelligent agents today attempt to mimic them, but they fall significantly behind in terms of efficiency, effectiveness, and reliability. The Active Generative Agents (AGA) Lab at the UNIST Graduate School of AI aims to investigate the principles underlying intelligence and apply them to build intelligent systems that can interact with the world actively, efficiently, and safely.
AGA Lab is primarily interested in developing principled methods at the intersection of generative modeling and reinforcement learning. We apply our algorithms to various high-impact real-world applications, including, but not limited to, robotics foundation models, biochemistry, particle physics, chemical engineering, and adtech.
Descartes, Principles of Philosophy, 1644
Principal Investigator: Sangwoong Yoon
I am an Assistant Professor at UNIST Graduate School of AI, jointly affiliated with the Department of Electrical Engineering. I was previously a Research Fellow at University College London (UCL) and Korea Institute for Advanced Study (KIAS). I also worked as a research scientist intern at Amazon (Seattle, US) and Kakao Brain.
Ph.D. in Mechanical Engineering, Seoul National University
M.S. in Neuroscience, Seoul National University
B.S. in Chemical and Biological Engineering, Seoul National University
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News
We are hiring! See Recruiting
Mar 2026: Sangwoong gives a talk, Generative Modeling and Reinforcement Learning: Energy, Reward, and Value, at UNIST AIGS Seminar
Feb 2026: Sangwoong gives a tutorial session at 2026 AI Winter School (2026 인공지능 동계단기강좌) hosted by Korea Artificial Intelligence Association
Jan 2026: wd1: Weighted Policy Optimization for Reasoning in Diffusion Language Models is accepted at ICLR 2026
Jan 2026: Robust Multi-Objective Controlled Decoding of Large Language Models is accepted at ICLR 2026
Jan 2026: Value Gradient Sampler: Learning Invariant Value Functions for Equivariant Diffusion Sampling is accepted at AISTATS 2026