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Bio-Inspired and Art-Inspired Electronics for Brain-Machine Interfaces

Xiao Yang, Ph.D.
Assistant Professor
Johns Hopkins University
Isermann Auditorium, CBIS, Rensselaer Polytechnic Institute
Thu, October 23, 2025 at 2:00 PM

Bioelectronic devices have been very important as fundamental research tools for probing and understanding the brain with high spatiotemporal resolution, and as therapeutic avenues for treating brain diseases, disorders, and injuries. However, they face notable challenges in achieving full biomimicry at the molecular level, expanded multifunctionality at the microscale, and versatile programmability at the macroscale. We drew inspiration from biological systems and art forms to design and develop a series of bio-inspired and art-inspired bioelectronics with distinctive biomedical applications. Our studies encompass neural probes for in vivo brain-machine interface, electronic scaffolds for brain repair, and platforms for detecting human genetic diseases and tracking human neural development using human brain organoids. Looking ahead, the Yang Lab aims to develop novel bioelectronics and biomaterials for brain-machine interfaces, regenerative medicine, and the study of human neural development and diseases.

Xiao Yang

Xiao Yang joined the Department of Biomedical Engineering at Johns Hopkins University as an Assistant Professor in June 2025. Prior to joining Johns Hopkins University, Dr. Yang was a Wu Tsai Neurosciences Institute Interdisciplinary Postdoctoral Scholar at Stanford University, working jointly in the laboratories of Professor Sergiu P. Pașca and Professor Bianxiao Cui. She received her Ph.D. in Chemistry from Harvard University under the guidance of Professor Charles M. Lieber in 2020, and her B.S. in Chemistry from the College of Chemistry and Molecular Engineering at Peking University in 2015. Dr. Yang drew inspiration from biological systems and art forms to design and develop a series of bio-inspired and art-inspired bioelectronics. Her studies encompass neural probes for in vivo brain-machine interface, electronic scaffolds for brain repair, and platforms for detecting human genetic diseases and tracking human neural development using human brain organoids.