Hyeonsu Lee, Ph.D.
Postdoctoral Researcher, Korea Institute of Science and Technology (KIST)
Hi, my name is Hyeonsu Lee. I earned my Ph.D. in Computational Neuroscience from KAIST (Aug 2024, advisor: Prof. Se-Bum Paik) and am currently continuing my research at KIST (advisor: Dr. Jaeson Jang). I hold a B.S. in Mathematical Sciences and an M.S. in Bio and Brain Engineering from KAIST, where I developed a deep interest in understanding how neural activity within small brain circuits can efficiently enable complex cognitive functions.
Recent News
- Jun 2025
Paper on continual learning published in Neural Networks
My mentee, Suhee Cho, and I recently published a paper presenting a metaplasticity model inspired by human working memory. In this study, based on my previous work (Lee et al., 2020), we implemented distinct types of synapses from stable to flexible, and randomly intermixed them to train synaptic connections with varying degrees of flexibility. We found that our model achieved a balanced tradeoff between memory capacity and performance without requiring additional training or structural modifications, dynamically allocating memory resources to retain both old and new information.
I am deeply grateful for the invaluable guidance and supervision of Prof. Se-Bum Paik.
- Oct 2024
Joined KIST as a postdoctoral researcher (Jang Lab)
I am excited to continue my research journey in a new place, KIST! I am deeply grateful to Dr. Jaeson Jang, my former colleague during my M.S. and Ph.D. years, for providing me with this opportunity to gain new experiences. Together, we aim to explore the emergence of cognitive functions and intriguing social behaviors in animal and human groups.
- Aug 2024Received Ph.D. in Bio and Brain Engineering from KAIST
- Jul 2024
Preprint on catastrophic forgetting posted on arXiv
My mentee, Suhee Cho, and I recently posted a preprint presenting a metaplasticity model inspired by human working memory. In this study, based on my previous work (Lee et al., 2020), we implemented distinct types of synapses from stable to flexible, and randomly intermixed them to train synaptic connections with varying degrees of flexibility. We found that our model achieved a balanced tradeoff between memory capacity and performance without requiring additional training or structural modifications, dynamically allocating memory resources to retain both old and new information.
I am deeply grateful for the invaluable guidance and supervision of Prof. Se-Bum Paik.
- Jul 2023
Paper on visual quantity comparison published in Cell Reports
Dr. Choi and I published a paper demonstrating the spontaneous emergence of quantity comparison ability. Our research showed that single neurons tuned to ratios and differences in visual quantities can arise spontaneously in completely untrained neural networks, enabling the network to perform quantity comparison tasks. I am deeply grateful for the guidance and supervision of Prof. Se-Bum Paik.
It was also introduced in several news outlets, including KAIST news.