 | A major contributor to this article appears to have a close connection with its subject.(July 2023) |
Mi Zhang | |
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Mi Zhang is a computer scientist at Ohio State University, where he is an Associate Professor of Computer Science and Engineering and the director of AIoT and Machine Learning Systems Lab. He is best known for his work in Edge AI, Artificial Intelligence of Things (AIoT), machine learning systems, and mobile health.
Zhang was born in Beijing, China. He received his B.S. degree in Electrical Engineering from Peking University in China. He received his M.S. degrees in both Electrical Engineering and Computer Science, and his Ph.D. degree in Computer Engineering, all from University of Southern California.
From 2013 to 2014, he was a postdoctoral associate in computing and information science at Cornell University. From 2014 to 2022, he was an assistant professor and then a tenured associate professor at Michigan State University. From 2022, he joined the Department of Computer Science and Engineering at Ohio State University as a tenured associate professor.
In 2016, he developed the first on-device deep learning-based pill identification algorithm on mobile devices that won the first place of the NIH Pill Image Recognition Challenge. [1]
In 2017, he developed the memory and computation-efficient AI-based real-time noise removal and speech enhancement algorithm for smart hearing aids that won the third place of the NSF Hearables Challenge. [2]
In 2019, he developed the model compression algorithms for enhancing the efficiency of deep learning models that won the 4th place of the CIFAR-100 track in the NeurIPS Google MicroNet Challenge. [3] [4]
In 2020, he won the MSU Innovation of the Year Award [5] for his smart hearing aids invention.
In 2021, he was awarded the ACM SenSys Best Paper Award. [6]
In 2023, he received the Inaugural USC ECE SIPI Distinguished Alumni Award in the Junior/Academia category for his contributions to mobile/edge computing in his early career. [7]
Some of his other notable awards include:
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