Jonathan Chau-Yan Kao

Jonathan Chau-Yan Kao is an Associate Professor in both Electrical and Computer Engineering and Computer Science at the University of California Los Angeles, affiliated with the Henry Samueli School of Engineering and Applied Science. His research bridges neural engineering, computational neuroscience, and artificial intelligence with a focus on brain-computer interfaces and neural decoding.

Dr. Kao's research interests center on understanding neural dynamics and developing advanced brain-computer interfaces. His work explores how neural populations encode information during motor control, decision-making, and cognitive processes. He investigates neural representations in various brain regions including the motor cortex, hippocampus, and periaqueductal gray, with applications ranging from motor prosthetics to understanding fear responses and pain processing. His research integrates computational modeling, machine learning techniques, and experimental neuroscience to decode neural activity and develop next-generation neural interfaces.

Analysis of Dr. Kao's publication record reveals a strong trajectory in neural engineering with increasing focus on brain-computer interfaces incorporating artificial intelligence. His work spans fundamental neuroscience investigations of neural coding principles to applied engineering of neural prosthetics. Recent publications show a clear trend toward developing AI-enhanced brain-machine interfaces and exploring neural representations across multiple brain regions during complex behaviors.

• NIH R01NS121097: An Open Source Simulator for Multi Degree-Of-Freedom Brain-Machine Interfaces (2021-2025), Principal Investigator
• NIH DP2NS122037: Next generation brain-machine interfaces controlled synergistically with artificial intelligence (2020-2025), Principal Investigator

Dr. Kao collaborates extensively with researchers across neuroscience and engineering disciplines, particularly with Avishek Adhikari's lab and other UCLA neuroscience groups. His research program demonstrates strong translational potential, bridging fundamental neural mechanisms with clinical applications for neurological conditions.