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Director of EdgeAI Lab
Associate Professor
The Department of Electrical & Computer Engineering
Herbert Wertheim College of Engineering
Office: MALA 4124
mingyueji@ufl.edu
Phone:

Google Scholar Profile, ORCID, ResearchGate, YouTube, GitHub

My research interests lie in the fascinating intersection of machine learning, distributed computing and storage, communication and networking, and information theory. In particular, we are focusing on developing AI algorithms and edge hardware platforms, applying AI to IoT, wireless sensing and wireless networking, and understanding the fundamentals of AI from optimization and information theoretic perspectives.

Openings

We will have multiple PhD openings for Fall 2025 working in the general area of machine learning; cloud/edge computing; wireless communications, networking and sensing; information theory and coding. If you are interested, please send me an e-mail with your current CV or drop by my office. I will be happy to discuss. Please check samples of our research talks on our YouTube channel.

Short Bio and Research Interests

I am an Associate Professor in the Department of Electrical and Computer Engineering and the director of EdgeAI lab at the University of Utah. I received my PhD in 2015 at Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California (USC), Los Angeles, USA. I received my MS degrees in Electrical Engineering (focusing on wireless networks) from University of California, Santa Cruz and in Electrical Engineering (focusing on information and signal processing) at Royal Institute of Technology (KTH), Stockholm, Sweden, and obtained my Bachelor Degree in Communication Engineering at Beijing University of Posts and Telecommunications (BUPT), Beijing, China. Previously, I was a Staff II System Design Scientist at Broadcom Limited, San Diego.

Prof. Daniela Tuninetti from UIC, Prof. Hua Sun from UNT and myself delivered the tutorial on “Distributed Function Retrieval: a Storage and Privacy Perspective” at 2021 IEEE International Symposium on Information Theory (ISIT 2021) held (virtually) in Melbourne Australia in July 2021. The tutorial was scheduled for July 16th 2021, MDT. The video can be found here and the slides can be found here.

News

  • (07/2024) Starting in August 2024, I will join the Department of Electrical and Computer Engineering at the University of Florida as an Associate Professor.
  • (07/2024) New Journal Paper on Privacy in Federated Learning Accepted by IEEE Transactions on Information Theory, Congratulations, All!!
  • (06/2024) Prof. Daniela Tuninetti from UIC, Prof. Hua Sun from UNT and myself delivered a tutorial titled “Secure Private Cache-aided Distributed Function Retrieval” on June 9th, 2024, at the 2024 IEEE International Conference on Communications (ICC).
  • (05/2024) New Paper on the Fundamentals of Data Heterogeneity in Federated Learning Accepted by ICML 2024, Congratulations, All!!
    • A New Theoretical Perspective on Data Heterogeneity in Federated Averaging, J. Wang, S. Wang, R.-R. Chen and M. Ji.