Fangqiang Ding

about me

I am a Postdoctoral Associate at MIT, working with Dr. Hermano Igo Krebs, director of The 77 Lab. Before MIT, I worked with Dr. Or Litany at Technion as a Postdoctoral Fellow. I was honored to be awarded a 2025 RSS Pioneer for my work on robust spatial perception for mobile robotics. I received my Ph.D. in Robotics and Autonomous Systems from School of Informatics, The University of Edinburgh, supervised by Dr. Chris Xiaoxuan Lu, and my B.Eng. in Mechanical Engineering from Tongji University.

🎯 My research agenda centers on Physical AI, which integrates advanced artificial intelligence with physical systems (e.g., self-driving cars, robots, wearables, industrial and IoT devices) to enable them to perceive, reason, and interact with the physical world. My long-term vision is a human-machine symbiotic ecosystem where human and embodied intelligence coexist, collaborate and co-evolve.

🚀 Achieving this vision requires systems that are not only increasingly capable, but also trustworthy and scalable in the real world. Trustworthy systems operate safely, reliably, and robustly across diverse environments and tasks, while protecting human privacy and aligning with human values. Scalable systems can be developed and deployed efficiently at scale through more affordable sensing and computation, as well as data collection, annotation, and learning pipelines. These core values motivate my research to address three key challenges, i.e., condition-adaptive, privacy-aware, cost-effective, for real-world deployment.

💡 My recent and ongoing research directions include (but not limited to):

• Multisensory perception for reliable mobile autonomoy in the wild
• Generalized human motion and interaction sensing in real world
• Long-horizon robotic (loco-)manipulation across tasks and environments
• Building deployable data flywheel for scalable robot learning

🤝 If you are interested in these directions and would like to explore collaboration opportunities, please feel free to reach out via email. Email · Resume · Google Scholar