Prof. Jooyeon Kim

I am an assistant professor at AIGS, UNIST. I strive to derive human-like machine intelligence from interactive and autonomous learning experiences. I focus on exploiting/uncovering the merits of Bayesian learning that provides principled way of allowing machine intelligence to adapt and generalize to unseen data/environments in conjunction with the deep learning models and frameworks.

Personal homepage: https://jyscardioid.github.io/

Yunpyo An

He is currently pursuing Ph.D degree at Ulsan National Institute of Science and Technology (UNIST). He graduated Cum Laude with a B.Sc. in Computer Science and Engineering from UNIST in 2022. His research focus on robust machine learning.

Webpage: raon1123.github.io

Contact: anyunpyo `at` (UNIST domain)

Joonsong Lee

Youngeun Cha

She is currently pursuing M.S. degree at Artificial Intelligence Graduate School (AIGS), Ulsan National Institute of Science and Technology (UNIST). She strives to develop and leverage learning methods that enable agents to understand their surroundings more efficiently and generalize beyond their training experiences. As part of this effort, she is recently interested in World Models and Reinforcement Learning.

Jiyun Kim

She is currently pursuing M.S. degree at the Artificial Intelligence Graduate School (AIGS), Ulsan National Institute of Science and Technology (UNIST). Her research interests lie in Reinforcement Learning, World Models, and Multi-Agent Systems, with a focus on developing intelligent agents that can learn to interact with and adapt to complex environments

Dongyun Kim

Researches multi-agent reinforcement learning to develop expert-level AI systems in which multiple agents coordinate and compete to solve complex tasks. Uses games and simulated environments as testbeds to study robust policies and zero-shot cooperation, aiming for agents that can reliably collaborate with diverse partners

Dayeon Hwang

Major: Computer Science and Engineering

Sophomore intern