Chaoming Wang

Ph.D., Principal Investigator

• wangchaoming@gdiist.cn

• 929-242-6868

Dr. Chaoming Wang is the Principal Investigator of the Laboratory for Large-Scale Brain Simulation. He received his Bachelor’s degree from Beijing Jiaotong University in 2018 and his Ph.D. degree from Peking University in 2023. From 2023 to 2025, he served as a Boya Postdoctoral Fellow at Peking University. He has been the principal investigator for projects funded by the National Natural Science Foundation of China (Youth Program) and the China Postdoctoral Science Foundation (General Program). Dr. Wang’s research focuses on the software, algorithms, and models for large-scale brain simulation. His related research has been published in over 10 high-level journals and top-tier AI conferences, including Nature Communications, eLife, Cell Reports, and ICLR, and he has been granted multiple national invention patents.

He has led the development of several original Chinese brain dynamics modeling frameworks, including: (1) the BrainPy framework, which implements a just-in-time compiled multi-scale brain dynamics programming system, significantly improving the computational efficiency of brain modeling; (2) the BrainUnit/SAIUnit system, which introduces standardized physical units into high-performance AI computing architectures, substantially enhancing the accuracy, maintainability, and physical interpretability of brain modeling; (3) the BrainTaichi framework, which provides sparse computation and event-driven operator programming capabilities, effectively reducing computational complexity; and (4) the BrainScale system, which achieves online learning of spiking neural networks with linear memory complexity O(N). These tools collectively form a multi-scale, differentiable modeling toolchain, realizing the deep integration of AI computing frameworks and brain simulation techniques.

Furthermore, his research work have been supported by the National Science and Technology Innovation 2030-Brain Science and Brain-inspired Intelligence Project and have received the OpenI Community Outstanding Project Award for two consecutive years (2021/2022).