About

Dr. Mo Li is a pioneering researcher at the intersection of autonomous materials discovery, intelligent optoelectronics, and advanced robotics. His most impactful work introduces a paradigm shift in materials science through "on-the-fly closed-loop materials discovery via Bayesian active learning" (325 citations), where he integrates machine learning with automated experimentation to dramatically accelerate the identification of novel materials. In optoelectronics, Dr. Li developed a "programmable black phosphorus image sensor for broadband optoelectronic edge computing" (219 citations), enabling in-sensor computing that reduces latency and power consumption for machine vision—a critical advancement for distributed robotics and autonomous systems. He further contributed to LiDAR technology with a "frequency–angular resolving LiDAR using chip-scale acousto-optic beam steering" (130 citations), enhancing spatial resolution for autonomous navigation. In robotics, Dr. Li has advanced exoskeletons through motion intention prediction (48 citations) and multirobot air combat via spatiotemporal relationship learning (12 citations). His work spans from fundamental materials discovery to applied intelligent systems, demonstrating a rare ability to bridge disciplines and drive innovation from the lab bench to real-world deployment.

Research Focus

Key Achievements

6
H-Index
7
Papers
745
Total Citations
106
Avg Citations/Paper
🏆 Most Cited Paper
On-the-fly closed-loop materials discovery via Bayesian active learning
325 citations
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 41
🏛 Institutions: University of Washington, Harbin Institute of Technology, Beijing Institute of Technology, Queen's University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago