Mi Zhang's Profile Picture

Mi Zhang

Associate Professor
Department of Electrical and Computer Engineering
Department of Computer Science and Engineering
Department of Biomedical Engineering
Michigan State University

mizhang [at] egr [dot] msu [dot] edu
(517) 432-4682
Office: 3530 Engineering Building (Map)
Lab: 1228 Engineering Building


I am the Director of Machine Learning Systems (MLSys) Lab at Michigan State University. My students and I work on topics at the intersection of systems and AI/machine learning, with current focus on On-Device AI for mobile, AR, robots, IoT (TinyML), and distributed edge systems, Automated Machine Learning (AutoML), Federated Learning and Privacy-Preserving Machine Learning, Systems for Machine Learning, Machine Learning for Systems, and Human-Centered AI for Health and Social Good.

My group has multiple open positions for PhD, masters, and undergraduates. Please send me your CV if you are interested.

Short Bio
: I received my B.S. in Electrical Engineering and a minor in Computer Science from Peking University in China. I received my Ph.D. in Computer Engineering and M.S. in both Electrical Engineering and Computer Science from University of Southern California (USC). Before joining MSU, I was a Postdoctoral Associate in Computing and Information Science at Cornell University.

Professional Services: This year, I serve on the program committee for the following venues: AAAI | ICLR Workshop on Neural Architecture Search | ICLR Workshop on Distributed and Private Machine Learning | ICML Workshop on Challenges in Deploying and Monitoring Machine Learning Systems | ACM SenSys | ACM/IEEE IoTDI | ACM HotMobile | EWSN. Please consider submitting your best work.

Selected Recent Invited Talks:

Recent Awards

  • 2020
    : Facebook Faculty Research Award
  • 2020
    : Best Paper Award, NeurIPS'20 Federated Learning Workshop
  • 2020
    : Best Paper Award Nominee, ACM/IEEE SEC'20
  • 2020
    : MSU Innovation of the Year Award
  • 2019
    : Amazon AWS Machine Learning Research Award
  • 2019
    : Google MicroNet Challenge (CIFAR-100 Track) 4th Place Winner @ NeurIPS'19
  • 2019
    : Best Paper Award Nominee, ICCV'19 Neural Architects Workshop
  • 2019
    : Google Security Reward
  • 2018
    : Best Paper Award, IEEE CNS'18
  • 2017
    : NSF Hearables Challenge Third Place Winner
  • 2017
    : NIH Mobile Health (mHealth) Scholar
  • 2016
    : NSF CRII Award
  • 2016
    : NIH Pill Image Recognition Challenge First Place Winner
  • 2015
    : Best Paper Award Honorable Mention, ACM UbiComp'15
  • 2015
    : All-Time Top Article, JMIR

Recent News


Our research is generously supported by the following federal agencies and industry partners. We express our sincere gratitude to their support.


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