Neuro-Artificial Intelligence Laboratory, Department of Physiology, Pusan National University School of Medicine. We work at the intersection of neuroscience and artificial intelligence: biologically grounded reinforcement learning, computational models of the brain and its disorders, AI-driven drug discovery, and clinical decision support.
We are recruiting undergraduate interns and graduate students. See Join.

Lee H. Noise Resilience of Successor and Predecessor Feature Algorithms in One- and Two-Dimensional Environments. Sensors. 2025; 25(3):979. https://doi.org/10.3390/s25030979
We compared the ability of SF and PF, reinforcement learning algorithms associated with the hippocampus of the brain, to reliably navigate noisy environments.
Investigating Transfer Learning in Noisy Environments: A Study of Predecessor and Successor Features in Spatial Learning Using a T-Maze https://mdpi.com/2983828