People

Sungho Hong is a Senior Research Fellow in the Center for Memory and Glioscience at the Institute for Basic Science (IBS), where he leads the Neuroscience-inspired AI group. He also holds appointments as Associate Professor in the IBS School at University of Science and Technology (UST) and Adjunct Professor in the Department of Biomedical Engineering at UNIST. Before joining IBS in 2024, he served as a Postdoctoral Researcher (2007–2012) and Group Leader (2012–2024) in the Computational Neuroscience Unit at Okinawa Institute of Science and Technology, Japan. Previously, he was a Senior Fellow in the Department of Physiology and Biophysics, University of Washington, USA, during 2004–2007. He is a theoretical physicist by training and received his PhD in Physics from University of Pennsylvania in 2004. His research interests, broadly speaking, lie in uncovering biophysical underpinnings of computations performed by neural systems. He has been conducting computational modeling studies in collaboration with experimental neuroscientists to work on various topics ranging from single neuron computation to circuit-level mechanisms for circadian rhythm and cerebellum-dependent sensorimotor learning. His current research explores the interface between neuroscience and artificial intelligence (AI) research, focusing on the cerebellum and its interactions with other brain regions.

Jungjoon Park is a Postdoctoral Researcher in the NeuroAI group at the IBS Center for Memory and Glioscience. Following his Ph.D. in Bio and Brain Engineering from KAIST (2022), he translated his systems and behavioral neuroscience expertise into practice by co-founding an AI startup for automated animal behavior analysis, and subsequently advanced next-generation multimodal behavior models as a postdoctoral researcher at KAIST AMILab. His research bridges behavioral neuroscience and multimodal AI to decode context-dependent information processing in both brain and behavior. He is particularly focused on how the principles of system consolidation—balancing episodic specificity with semantic generalization—and social cognition (e.g., empathy, Theory of Mind) can inspire cognitive architectures capable of cumulative learning and robust adaptive intelligence.