Curriculum Vitae
Hyeonsu Lee, Ph.D.
Postdoctoral Researcher, Korea Institute of Science and Technology (KIST)
Seoul, Republic of Korea
hyeonsu.lee@kist.re.kr · hyeonsu.lee.93@gmail.com · Google Scholar
Seoul, Republic of Korea
hyeonsu.lee@kist.re.kr · hyeonsu.lee.93@gmail.com · Google Scholar
Research Interests
Computational Neuroscience · Mathematical Modelling · Neural Data Analysis
Education
2018–2024
Ph.D. in Bio and Brain Engineering, KAIST, Korea
Advisor: Se-Bum Paik
2016–2018
M.S. in Bio and Brain Engineering, KAIST, Korea
Advisor: Se-Bum Paik
2011–2016
B.S. in Mathematical Sciences, KAIST, Korea
Business and Technology Management (Minor)
Research Experience
2024–present
Postdoctoral researcher, KIST (Advisor: Jaeson Jang)
Multi-agent model simulation (LLM, agent-based, etc.)
Data analysis (human/animal behaviors, mouse proteomics)
2016–2024
Graduate researcher, KAIST (Advisor: Se-Bum Paik)
Neural circuit modeling of visual cognitive functions
Interpret behavioral data via reinforcement learning
Neural data analysis: Spike, LFP, Calcium imaging, etc.
2015–2016
Research intern, KAIST
Modeling visual system-like image compression algorithm
2014
Researcher, ybrain
Design clinical trials (AD and MDD), Neural data analysis, Human psychophysical experiments
2013
Research intern, KAIST
Analyzing functional brain imaging (DWI)
Journal Articles
* co-first, † co-corresponding author
2025
[J6] Cho S, Lee H, Baek S & Paik SB. Neuromimetic metaplasticity for adaptive continual learning without catastrophic forgetting. Neural Networks (2025). doi
2023
[J5] Lee H*, Choi W*, Lee D & Paik SB. Comparison of visual quantities in untrained neural networks. Cell Reports (2023). doi
2021
[J4] Jeong M*, Lee H*, …, Paik SB†, Lim BK† & Kim D†. Interhemispheric cortico-cortical pathway for sequential bimanual movements in mice. eNeuro (2021). doi
[J3] Bae JW*, Jeong H*, …, Lee H, Paik SB & Jung MW. Parallel processing of working memory and temporal information by distinct types of cortical projection neurons. Nature Communications (2021). doi
2020
[J2] Lee H, Choi W, Park Y & Paik SB. Distinct role of flexible and stable encodings in sequential working memory. Neural Networks (2020). doi
2018
[J1] Song M*, Kang MS*, Lee H, Jeong Y & Paik SB. Classification of spatiotemporal neural activity patterns in brain imaging data. Scientific Reports (2018). doi
Preprints / Under Review
2026
[P2] Cho Y*, Lee H*, Deneuville E & Jang J. Learning from Natural Images Untangles Number Sense. Under review (2026).
2020
[P1] Choi W, Lee H & Paik SB. Slow rhythmic eye motion predicts periodic alternation of bistable perception. bioRxiv (2020). doi
Selected Conference Presentations
2026
[S4] Cho Y*, Lee H*, Deneuville E & Jang J. Separating numerosity and proportion representations through pretraining. CCN 2026.
2025
[S3] Lee H, Baek S, Choi W, Jang J & Paik SB. Spontaneous social tipping and trend cycles driven by randomness. SfN 2025.
2022
[S2] Choi W*, Lee H* & Paik SB. Spontaneous emergence of magnitude comparison units in untrained deep neural networks. Cosyne 2022.
2018
[S1] Lee H, Choi W, Park Y & Paik SB. Resource overwrite model for sequential working memory in human. SfN 2018. (Oral)
Patents
2024
[PAT2] Paik SB, Cho S, Lee H, Baek S. Method for addressing catastrophic forgetting in artificial neural networks using neuromimetic metaplasticity rules observed in natural brains. KR Patent, 10-2024-0199987 (2024).
생물학적 두뇌의 메타가소성 법칙을 적용하여 인공신경망 학습에서 파괴적 망각을 해결하는 방법 및 장치
2022
[PAT1] Paik SB, Lee H, Park Y. Storage device using neural network and operating method for automatic redistribution of information and variable storage capacity based on accuracy-storage capacity tradeoff thereof. US Patent, US 11,467,728 B2 (2022). link
신경망을 이용한 기억 장치 및 그의 정확성-저장용량 트레이드오프에 기반한 정보의 자동적 재분배 및 가변적 용량 구현을 위한 동작 방법
Conference Presentations
International
2026
[C22] Cho Y*, Lee H*, Deneuville E & Jang J. Training on natural images disentangles interfering numerical codes in deep neural networks. KSBNS 2026.
[C21] Cho Y*, Choi S*, Lee H & Jang J. Reducing high-density EEG channels while preserving depression-related ERP signatures. KSBNS 2026.
[C20] Cho Y*, Lee H*, Deneuville E & Jang J. Pretraining on natural images separates numerosity and proportion representations. FENS 2026.
2025
[C19] Lee H, Baek S, Jang J & Paik SB. Spontaneous social change driven by Stochastic Individual Behavior. KSBNS 2025.
2023
[C18] Lee H & Paik SB. Emergence of aesthetic preferences in untrained deep neural networks. SfN 2023.
[C17] Kim G, Kang M, Lee H, Park Y, Song M & Paik SB. Random imitation as an efficient survival strategy in multi-agent systems. SfN 2023.
[C16] Kang M, Kim G, Lee H, Park Y, Song M & Paik SB. Random imitation as an evolutionary strategy in a multi-agent system. KSBNS 2023.
2022
[C15] Lee H*, Choi W*, Lee D & Paik SB. Quantity comparison in untrained deep neural networks. SfN 2022.
[C14] Kang M, Lee H, Park Y, Song M & Paik SB. Random imitation for evolution in multi-agent systems. SfN 2022.
[C13] Lee H*, Choi W*, Lee D & Paik SB. Comparison of visual quantities in untrained deep neural networks. CNS 2022.
[C12] Lee H*, Choi W*, Lee D & Paik SB. Visual quantity comparison in untrained deep neural networks. KSBNS 2022.
2021
[C11] Lee H*, Choi W* & Paik SB. Visual proportion sense in untrained deep neural networks. SfN 2021.
2020
[C10] Bae JW, …, Lee H, Paik SB & Jung MW. Distinct types of cortical projection neurons for working memory and timing. KSBNS 2020.
[C9] Choi W, Lee H & Paik SB. Rhythmic eye movement predicts active perception of ambiguous visual stimulus. CNS 2020.
2019
[C8] Jeong M, Lee H, …, Lim BK, Paik SB & Kim D. Neuronal ensemble encoding bimanual motor coordination in mice. SfN 2019.
2018
[C7] Lee H, Choi W, Park Y & Paik SB. A dynamic resource model for sequential working memory. CNS 2018.
2017
[C6] Lee H, Choi W & Paik SB. Working memory pre-allocation improves the performance of sequential memory task. KSBNS 2017. (Best Presentation Award)
[C5] Lee H*, Park Y* & Paik SB. Pre-allocation of memory resources improves working memory performance in a sequential memory task. SfN 2017.
[C4] Lee H, Choi W & Paik SB. Pre-allocation of working memory modulates memory performance. CNS 2017.
2016
[C3] Choi W, Lee H & Paik SB. Local disinhibition modulates brain functions by mediating global network state. SfN 2016.
[C2] Song M*, Kang M*, Lee H, Lee H, Jeong Y† & Paik SB†. Spatio-Temporal Classification of Neural Activity Patterns in Dynamic Brain Imaging Data. SfN 2016.
[C1] Song M, Lee H & Paik SB. Quantitative Classification of Neural Network Activity Patterns in Imaging Data. CNS 2016.
Domestic
2026
[D10] Cho Y*, Lee H*, … & Jang J. Natural image pre-training disentangles distinct quantity representations. cbrain 2026.
[D9] Cho Y*, Choi S*, Lee H & Jang J. Reducing high-density EEG to extract a minimal ERP feature set for depression classification. cbrain 2026.
2025
[D8] Lee H, Baek S, Jang J & Paik SB. Emergent Cycles in Social Behavior from Stochastic Individuals. cbrain 2025.
2018
[D7] Lee H, Choi W, Park Y & Paik SB. Sequential overwrite model can explain the serial-position effects in working memory. KSCS 2018.
[D6] Lee H, Choi W, Park Y & Paik SB. A theory of resource allocation for sequential memory in human. KPS 2018.
2017
[D5] Lee H, Choi W & Paik SB. Working memory resource allocation improves the sequential memory performance. cbrain 2017.
[D4] Lee H, Choi W & Paik SB. A comparative study on simultaneous versus sequential presentation of stimuli for working memory performance. KPS 2017.
2016
[D3] Song M, Lee H & Paik SB. Computational Classification of Neural Network Activity Patterns for Imaging Data. KPS 2016.
2015
[D2] Lee H*, Song M* & Paik SB. Classification of the Neural Activity Patterns by Spatio-Temporal Correlation Index. cbrain 2015.
[D1] Lee H, Jang J & Paik SB. A Biologically Inspired Adaptive Model for Efficient Image Compression. KPS 2015.
Honors and Awards
2025
Poster Presentation Awards, Brain Science Institute of KIST
2018
Best TA awards, Bio and Brain Engineering, KAIST
2017
Best Presentation Awards, Korean Society for Brain and Neural Sciences (KSBNS)
2017
Poster Presentation Awards, Korean Society for Computational Neuroscience (cbrain)
Skills
Brain-inspired AI, Python, MATLAB, Illustrator
Neural network modeling & simulation, Data analysis, Mathematical modeling, Dynamical systems modeling
LLM simulation, Multi-agent simulation, Human psychophysical experiment, Eye-tracking
Last updated: November 2026