个人简历：
Dr. Yanming Zhu is a Tenure-track Assistant Professor at the School of Biomedical Engineering at ShanghaiTech University and the Shanghai Clinical Research and Trial Center, where he also directs the Mechanisms of Intracranial Neural Dynamics Laboratory (MIND Lab).
Dr. Zhu’s research primarily focuses on neurosurgery, neural engineering, brain-computer interfaces (BCIs), and the mechanisms underlying human brain function. He is dedicated to advancing next-generation neuromodulation, BCItechnologies, and intelligent neurosurgical diagnostic and therapeutic techniques by tackling clinical challenges as a starting point, leveraging research into human brain mechanisms as a fulcrum, and utilizing innovative engineering technologies as the pathway.
Dr. Zhu completed his undergraduate and medical training at the Shanghai Medical College of Fudan University. He subsequently earned both a Ph.D. and an M.A. from Harvard University, followed by systematic clinical and research training in neurosurgery at Massachusetts General Hospital, the University of California, San Francisco (UCSF), and Huashan Hospital affiliated with Fudan University. His research integrates high-density electrocorticography, single-neuron recording, machine learning, and neuromodulation techniques to conduct interdisciplinary investigations into topics such as language, audition, olfaction, higher-order cognitive functions, deep brain stimulation for Parkinson's disease, and the translational application of brain-computer interfaces.
Dr. Zhu has published numerous articles in leading academic journals, including Nature Human Behavior, Nature Communications, Science Advances, and Neurosurgery Clinics of North America. He actively participates in academic exchanges both domestically and internationally, having delivered presentations at major conferences in neuroscience, neurosurgery, neurolinguistics, and brain-computer interfaces.
研究领域：
Functional Neurosurgery (Movement Disorders, Epilepsy, etc.)
Brain-Computer Interfaces
Sensory Encoding and Modulation in the Brain
Higher Cognitive Functions of the Brain
教学与课程：
Brain-Computer Interfaces, Neuroengineering, and Artificial Intelligence
学术任职：
代表性论文：
Zhu, Y., Xu, M., Lu, J., Hu, J., Kwok, V. P., Zhou, Y., ... & Tan, L. H. (2022). Distinct spatiotemporal patterns of syntactic and semantic processing in human inferior frontal gyrus. Nature Human Behaviour, 6(8), 1104-1111.
Zhu, Y., Richardson, R., Bush, A., Vissani, M., & Bullock, L. (2025). Human subthalamic neurons encode speech features during listening and couple with auditory cortex.
Zhu, Y., Lajoie, Z., Hadanny, A., Kons, Z., ... Costanzo, Bush, A. & Richardson, R. (2026). Gamma activity temporally dissociates sensory encoding from perceptual decision-making in human olfactory circuits.
Jiang, S.*, Zhu, Y.*, & Hu, J. (2024). The value of stereo-electroencephalography in temporal lobe epilepsy: huashan experience. Neurosurgery Clinics, 35(1), 95-104.
实验室介绍：
Mechanisms of Intracranial Neural Dynamics Laboratory
MIND Lab
The Mechanisms of Intracranial Neural Dynamics Laboratory (MIND Lab) aims to leverage the unique resources of the School of Biomedical Engineering at ShanghaiTech University and the Shanghai Clinical Research and Trial Center. Focusing on major clinical needs in neurosurgery and fundamental questions in cognitive neuroscience, the laboratory conducts interdisciplinary research centered on a continuum spanning Clinical problems - Neural mechanisms - Engineering innovation - Intelligent diagnosis and treatment - Translational application. By integrating functional neurosurgery, human intracranial electrophysiology, artificial intelligence, and closed-loop neuromodulation technologies, the laboratory seeks to establish a research platform for human brain studies and brain-computer interfaces characterized by distinct clinical relevance and robust engineering translational capabilities.
The lab’s primary research directions include: (1) utilizing human intracranial electrophysiological recordings to elucidate the neural mechanisms underlying language, audition, olfaction, motor control, and higher-order cognitive functions; (2) developing brain-computer interface algorithms and systems aimed at the functional restoration of speech, motor control, and sensory perception; (3) developing next-generation brain-computer interfaces and precision neuromodulation devices; and (4) integrating machine learning with multimodal clinical data to establish AI-assisted methods for neurosurgical diagnosis, treatment, and the optimization of neuromodulation parameters. The laboratory is committed to actively fostering multidisciplinary collaborations with hospitals, engineering schools, industry partners, and translational platforms, thereby forging a continuous innovation chain that extends from the discovery of fundamental mechanisms to clinical validation and industrial translation.
