Seungjae Han

Computational Neuroscience · Machine Learning

I am a Ph.D. student at KAIST (NICA Lab), advised by Professor Young-Gyu Yoon. My work develops computational methods for large-scale neural recordings, spanning acquisition, denoising, and quantitative interpretation of brain-wide optical data. I am broadly interested in bridging measurement and inference by designing algorithms that are robust under noise and distribution shift, computationally efficient, and scientifically interpretable.

My research includes self-supervised microscopy denoising and video processing, with publications in Nature Methods (cover article, 2023) and Nature Electronics (2025), alongside contributions in computer vision and computational imaging. I received the SfN Trainee Professional Development Award (2023), the AKN Outstanding Research Award (2023), and the KAIST Outstanding Paper Award (2024), and Top Reviewer Recognition at NeurIPS (2024).