Lei Ma
Principal Investigator / Assistant Professor / Ph.D. Advisor
Director, Digital Life Simulation Lab
Deputy Director, Department of Big Data and Biomedical AI, Peking University
Director of Platform IV, Multimodal Trans-scale Biomedical Imaging Facility
College of Future Technology, National Biomedical Imaging Center (NBIC)，Peking University
Dr. Lei Ma is a principal investigator at the National Biomedical Imaging Center, Peking University. His research lies at the intersection of artificial intelligence and life sciences, with a particular focus on Digital Life , the construction of executable and verifiable computational models of biological systems across scales. Before joining Peking University, Dr. Ma worked at Autodesk Research, where he contributed to the development of core industrial software engines. In 2019, he founded the Life Simulation Research Center at Beijing Academy of Artificial Intelligence, leading efforts in digital organism modeling.
His work has been published in Nature Computational Science (Cover), Cell Research (Cover), Nature Communications, National Science Review, and other leading journals, with 90 SCI/EI papers in total (46 as first/corresponding author), with a cumulative impact factor exceeding 417. His work aims to advance a shift from predictive AI for biology toward reconstructive models of living systems—systems that can generate, simulate, and explain biological function through structure and interaction. He is a recipient of the Beijing Outstanding Youth Fund, and has been recognized as a BAAI Scholar, Berggruen Fellow, and Bayer Investigator.
Research
| Digital Worm (BAAIWorm) |
Built the first data-driven integrative model of C. elegans encompassing all 302 neurons, achieving closed-loop simulation of nervous system, body, and environment, with behaviors emerging naturally from biological structure. Nature Computational Science, 2024 (Cover) [Paper] |
| Neural Time Computation |
Revealed system-level time computation and representation mechanisms in the suprachiasmatic nucleus through large-scale calcium imaging and machine learning. Cell Research, 2024 (Cover) [Paper] |
| GPU Brain Simulation |
Developed a GPU-accelerated computational framework bridging biophysically detailed neuron simulation and AI training, enabling efficient simulation and optimization of large-scale neural models. Nature Communications, 2023 [Paper] |
| Digital Life Infrastructure |
Leading NBIC Instrument IV construction for trans-scale biomedical data integration. Initiated the Kidney Imageomics Project and the Panoramic Digital Life international science program. National Science Review, 2025 [Paper] |
Selected Publications
* Corresponding author, # Co-first author
M. Zhao, N. Wang, X. Jiang, X. Ma, H. Ma, G. He, K. Du, L. Ma*, T. Huang. An integrative data-driven model simulating C. elegans brain, body, and environment interactions. Nature Computational Science, 4(12): 978–990, 2024. Cover [Link]
Z. Wang, J. Yu, M. Zhai, et al., L. Ma*, W. Hu*, H. Cheng*. System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning. Cell Research, 34(7): 493–503, 2024. Cover [Link]
Y. Zhang#, G. He#, L. Ma#, et al., S. Grillner, K. Du, T. Huang. A GPU-based computational framework that bridges neuron simulation and artificial intelligence. Nature Communications, 14: 5798, 2023. [Link]
F. Zhou, Z. Li, et al., B. Dong*, L. Ma*, L. Yang*. An initiative on digital nephrology: the Kidney Imageomics Project. National Science Review, 2025. [Link]
L. Chen*, L. Ma*, H. Dai, Q. Du, Y. Sun, H. Cheng*. Trans-scale bioimaging and integrative biology: on the debut of China National Biomedical Imaging Center. Science China Life Sciences, 2025.
Contact & Openings
Email: Address: National Biomedical Imaging Center (NBIC), Peking University Lab: maleilab.cn
We are actively recruiting postdocs, Ph.D. students, master students, and research assistants. Current focus areas: Scientific Software & Platform Engineering, Scientific Computing & Closed-loop Simulation, Biomedical AI Systems.
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