JaeHeon Lee

At KAIST, where I’m currently in my 4th year, I majored in Biology, AI, and Electrical Engineering, building a foundation in computational neuroscience. I’m interested in how recurrent dynamics represent time-dependent information and support memory, while uncertainty modulates inference and decision-making, contributing to structured forms of complex cognition across multiple scales of neural organization. I’ve also studied mathematics by watching a YouTube channel.

I interned in Min Whan Jung’s lab for two months, assisting with rat experiments involving training and surgical procedures. Following that, I spent 1.5 years in Sang Wan Lee’s lab working on a simple RL project and analyzing error signal propagation in fMRI using MVPA. I also worked as a data scientist and a participant in Korea’s mandatory ITP program for two years at DeepBio, an AI histopathology startup. Currently, I’m part of Yul HR Kang’s lab (since Spring 2024), focusing on psychophysics and human uncertainty, as well as neural posterior estimation and cognitive map formation in computational models. Also, I’m working in Cristina Savin’s lab at NYU (since Fall 2024) on a project related to curriculum learning, investigating how models reuse neural dynamics when performing multiple tasks sequentially.

I will be joining John D. Murray’s lab at Dartmouth College as a PhD student in the Psychological and Brain Sciences program (Fall 2026), where I’ll continue investigating the computational principles underlying cognition and neural dynamics.

Thank you for visiting my GitHub page, where I share my pursuits and discoveries.

Best regards, JaeHeon Lee