Mingyue Ji

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Director of EdgeAI Lab
Associate Professor
The Department of Electrical & Computer Engineering
Adjunct Associate Professor
Kahlert School of Computing
John and Marcia Price College of Engineering, University of Utah
My Website at the U: http://faculty.utah.edu/~mingyueji/

Email: mingyue.ji@utah.edu
Offcie: MEB 3108
Phone: 801-587-7255
Google Scholar Profile, ORCID, ResearchGate, YouTube, GitHub


Announcement

Prof. Daniela Tuninetti from UIC, Prof. Hua Sun from UNT and myself will deliver a tutorial titled “Secure Private Cache-aided Distributed Function Retrieval” on June 9th, 2024, at the 2024 IEEE International Conference on Communications (ICC).

Openings

We have at least 2 PhD openings for Fall 2024 working in the general area of cloud/edge computing; machine learning; 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.

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.

News

  • (04/2024) Our Senior Clinic Project on the application of Edge AI sponsored by L3Harris and titled “Benchmarking Machine Learning Devices for Radio Frequency Spectrum Sensing” won the Most Innovative amd Societal Impact Awards in the Department of Electrical and Computer Engineering at the U.

    • The project poster can be found here.

    • See the Awards below.

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  • (07/2023) Two Papers Accepted in IEEE Asilomar 2023, Congratulations, All!!

    • Rethinking the Data Heterogeneity in Federated Learning, J. Wang, S. Wang. R.-R. Chen and M. Ji (invited paper).

    • A Novel Scheme for Cache-aided Multiuser Private Information Retrieval with User-to-user Privacy, X. Zhang, K. Wan, H. Sun, M. Ji and G. Caire.

  • (06/2023) Received INL grant titled “Multi-band Wireless Architecture for Nuclear Power Plants: University of Utah Research Scope”. Support from INL and DOE is gratefully acknowledged. This is a joint grant with Prof. Sneha Kumar Kasera (PI) from School of Computing, and with Dr. Vivek Agarwal from INL.

  • (06/2023) New ArXiv e-prints:

  • (06/2023) New Journal Paper Accepted by IEEE Transactions on Information Theory, Congratulations, All!!

  • (06/2023) New Paper Accepted by ICML 2023 Workshop FL, Congratulations, All!!

  • (04/2023) The second PhD student in C^3 group, Xiang Zhang, completed his defense with flying color. Congratulations!!

    • The in-person video can be found here.

    • The online video can be found here.

    • Here is a photo after his defense.

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  • (04/2023) Our Senior Clinic Project titled “Sensor-Scheduling Strategy in Electronic Support” won the Outstanding Electric Engineering Project Award.

    • See the group on stage below.

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  • (04/2021) Our senior design project on Coded Elastic Computing over Wireless Edge Computing Systems was a great success and Merek Goodrich won the Project Design Excellence award, Congratulations to Merek!!

    • See the Github page: here.

    • See a photo of Merek below.

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  • (04/2021) Our senior design project on Features Exchange in Federated Learning was a great success and Tiffany (Xintong) Liu won the Project Design Excellence award, Congratulations to Tiffany!! The paper will be uploaded very soon.

    • See a photo of Tiffany below.

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  • (04/2021) Our senior design project on Implementation of Gradient Coding over Raspberry Pis was a great success and Henry Crandall won the Project Design Excellence award, Congratulations to Henry!!

    • See the Github page: here.

    • See a photo of Henry below.

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  • (04/2020) Our senior design project on Coded Machine Learning was a great success and Michael Crabtree won the Project Design Excellence award, Congratulations to all (Michael Crabtree, Mary Richardson, Yu-Hsiang (Jerry) Hu)!!

    • See the project page: here.

    • See the presentation video: here.

    • See the demo video: here.

    • See a photo of Michael below.

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  • (04/2019) Our seninor design project on Edge Computing and Distributd Machine Learning (Federated Learning) was a success and won Outstanding Electrical Engineering Senior Project Individual Award (Collin Tate) and Outstanding Electrical Engineering Senior Presentation Award (David Moody). Congratulations to all!!

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From the right to the left: Keoki Daley, Joshua Nett, David Moody, Collin Tate, Justin Olsen and Mingyue Ji