Short Bio: Mi Zhang is an Associate Professor and the Director of AIoT and Machine Learning Systems Lab in the Department of Computer Science and Engineering at The Ohio State University (OSU). He received his Ph.D. degree from University of Southern California (USC) and B.S. from Peking University, and spent one year as a postdoctoral scholar at Cornell University. 

Research Areas: The key mission of Dr. Zhang's research lab is to bring the power of AI, in particular, deep learning, to Empowering Billions of Everyday Devices with AI to realize the vision of Artificial Intelligence of Things (AIoT). To achieve such mission, his group focuses on its core challenges related to sensing, intelligence, connectivity, efficiency, automation, scalability, privacy, and inclusiveness as well as its important applications such as healthcare and sustainability. Achieving such goal requires a combination of approaches. His work draws insights from a broad set of disciplines including mobile & embedded systems, AI/machine learning, wireless networking, distributed systems, and human-centered computing.

Specifically, Dr. Zhang and his students currently work on the following topics:

• Edge AI for mobile, AR (Metaverse), IoT as well as networked and distributed edge-cloud systems
• Federated Learning
• AI/Machine Learning for Systems (wireless networking, video analytics, sensing systems)
• Systems for AI/Machine Learning
• Mobile Health and Human-Centered AI (digital mental health, smart hearing aids, pill identification)
• Automated Machine Learning

Honors and Awards: Dr. Zhang is the 4th Place Winner (1st Place in U.S. and Canada) of 2019 Google MicroNet Challenge (CIFAR-100 Track), the Third Place Winner of 2017 NSF Hearables Challenge, and the champion of 2016 NIH Pill Image Recognition Challenge. He is the recipient of seven best paper awards and nominations. He is also the recipient of the NSF CRII Award, Facebook Faculty Research Award, Amazon Machine Learning Research Award, MSU Innovation of the Year Award, and the inaugural USC ECE SIPI Distinguished Alumni Award in the Junior/Academia category for his contributions to mobile/edge computing in his early career.

Recent Talks:

• Stanford University: Empowering the Next Billion Devices with Deep Learning, 2021.