MxW Workshop - Shanghai 2026

Dr. Shuai Jianwei is a professor at Wenzhou Institute, University of Chinese Academy of Sciences since 2023. He earned his doctoral degree from the Department of Physics, Xiamen University in 1995. He has previously worked at City University of Hong Kong, The University of Electro-Communications in Japan, Case Western Reserve University, Ohio University, and the University of California, Irvine from 1996 to 2007, respectively. In June 2007, he returned to China and was appointed as Minjiang Distinguished Professor at Xiamen University. His research interests cover the fused intelligence, intelligent mechanics, computational biomedicine, artificial intelligence, big data in healthcare, and biological multi-omics analysis. He has published over 260 papers in journals including Nature Cell Biology, Physical Review Letters, PNAS, and Nature Communications.

When AI Meets Mini-Brains: Card-Playing Brain Organoid Agents

Traditional brain-computer interfaces (BCIs) adopt static digital frameworks to decode neuronal networks, which fail to match the brain’s inherent neural coding mechanisms. Closing this compatibility gap is vital for treating neuronal disorders, optimizing brain function, and improving neuroprosthetic accuracy. Combining brain organoids with microelectrode arrays (MEA) creates a humanized in vitro BCI platform with superior biocompatibility for dynamic neuronal decoding. This study addresses the bio-electronic encoding incompatibility via three key advances. It first develops a human-machine hybrid platform integrating brain organoids, high-density MEAs and computational chips for closed-loop neuronal modulation. Second, it builds reconfigurable stimulation nodes to align with organoid electrophysiological states via neural plasticity, eliminating encoding mismatches. Lastly, it establishes the first scalable multi-agent interaction system (MAIS) under shared plasticity rules. Validated in pathological and normal neuronal network models, MAIS acts as a self-evolving neural coding sandbox, laying scalable foundational support for human-centric neural interfaces.

Decoding In Vitro Functional Neural Networks: From Pathophysiological Phenotyping of Brain Organoids to Establishing Novel Models