Faculty

Jinxing Li
Biomedical Engineering
Research Clusters: Microrobotics, Soft Robotics, Underwater Robotics

Bio: Jinxing Li is an assistant professor in the Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering. He joined MSU as part of the university’s Global Impact Initiative from Stanford University, where he did his postdoctoral research on engineering soft materials to make miniaturized devices for biomolecular sensing, neuromodulation, and adaptive locomotion. He received his Ph.D. in NanoEngineering at UC San Diego, where he developed a nanorobotic toolbox and pioneered the therapeutic use of micro/nanorobotics. He was a visiting scholar at Bell Labs working on wearable telemedicine devices. He received his B.S. in Huazhong University of Science and Technology and M.S. in Fudan University, both in Electrical Engineering. He is a recipient of Siebel Scholar of Bioengineering, Materials Research Society Graduate Student Award, Dan David Prize Scholarship, American Chemical Society Division of Inorganic Chemistry Young Investigator Award, MIT Technology Review Innovators Under 35, and 30 Rising Leaders in The Life Sciences.

Google Scholar Page: https://scholar.google.com/citations?user=Cd7lEf4AAAAJ&hl=en

Webpage: https://www.labli.net/

Tong (Tony) Gao
Associate Professor
Mechanical Engineering, Computational Mathematics Science and Engineering
Research Clusters: Learning for Decision and Control, Microrobotics, Multi-agent Systems, Nonlinear Dynamics and Control, Soft Robotics, Underwater Robotics

Bio: Dr. Tong (Tony) Gao is an Associate Professor at the Department of Mechanical Engineering and Department of Computational Mathematics, Science, and Engineering at Michigan State University, where he directs the Complex Fluids Group. He obtained his Ph.D. degree in Mechanical Engineering at the University of Pennsylvania in 2012. Then he worked as a research scientist in the Applied Mathematics Lab at the Courant Institute of Mathematical Sciences of New York University. Dr. Gao works in the interdisciplinary areas of soft condensed matter, fluid mechanics, and materials via mathematical modeling and high-performance computing. His expertise lies in constructing advanced computational mechanics models for fluid-solid systems with high complexities (e.g., many-body interactions) and nonlinearity (e.g., fluid/elastic structure interactions), and developing scalable simulation tools to promote data-driven, physics-informed studies. Dr. Gao received the NSF CAREER award in 2020. The current focused research topics include bioactive matter, soft robotics, and patient-specific medical models.

Webpage: https://www.egr.msu.edu/~gaotong/