Neuroscience PhD student at UNC Chapel Hill (BBSP)
Advised by Adam Hantman & Kanaka Rajan

Previously worked at:
– Metaconscious Lab, MIT
– BMI Lab, Seoul National University Hospital

Research Interests

• Artificial neural networks as computational neuroscience model
• Explainable deep neural networks
• Medical AI
• Synaptic plasticity & learning rules for artificial neural networks

Worked on

• Neuro-inspired reinforcement learning
• Continual learning
• AI in medical neuroscience
• Privacy-preserving deep learning.

Jaesung Yoo, Sunghyouk Choi, Ye Seul Yang, Suhyeon Kim, Jieun Choi, Dongkyeong Lim, Yaeji Lim, Hyung Joon Joo, Dae Jung Kim, Rae Woong Park, Hyeong-Jin Yoon, Kwangsoo Kim. Review learning: Real world validation of privacy preserving continual learning across medical institutions. Computers in Biology and Medicine (2025). (Paper, Preprint)

Jaesung Yoo, Fernanda de la Torre, Robert Guangyu Yang. Dual policy as self-model for planning. Journal of Korean Institute of Intelligent Systems (2024). (Paper, Preprint, Github)

Jaesung Yoo*, Ilhan Yoo*, Ina Youn, Sung-Min Kim, Ri Yu, Kwangsoo Kim, Keewon Kim, Seung-Bo Lee. Residual one-dimensional convolutional neural network for neuromuscular disorder classification from needle electromyography signals with explainability. Computer Methods and Programs in Biomedicine (2022). (Paper, Github)
(Achieved the highest CLAIM score in an AI-based nEMG review by S. de Jonge et al. (2024).)

Ilhan Yoo*, Jaesung Yoo*, Dongmin Kim, Ina Youn, Hyodong Kim, Michelle Youn, Jun Hee Won, Woosup Cho, Youho Myong, Sehoon Kim, Ri Yu, Sung-Min Kim, Kwangsoo Kim, Seung-Bo Lee, Keewon Kim. Deep learning model for needle electromyography electrodiagnosis in comparison with physician assessment: A retrospective study. (Preprint)