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 (MSU). My students and I work on topics at the intersection of systems and Artificial Intelligence/machine learning, with current focus on On-Device AI for mobile, AR/VR, IoT (TinyML), and distributed edge systems, Automated Machine Learning (AutoML), Federated Learning, Systems for Machine Learning, Machine Learning for Systems, and AI for Health.

My group has open positions for PhD students, 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.

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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