Minjia Zhang
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Education
- Ph.D. - Computer Science and Engineering - Ohio State University, USA, 2016
Academic Positions
- Tenure-Track Assistant Professor, Computer Science Department, Univ. of Illinois
Other Professional Employment
- Principal Researcher - Microsoft Research and AI, Redmond, WA, 2016-2023
Research Interests
- Large-scale DL/AI applications (Agentic AI, MultiModal, Image/Video Generation, etc)
- Effective efficiency algorithms (Model compression, data efficiency, parameter-efficient tuning, etc.)
- Efficient Machine Learning Systems (Training/inference on parallel/distributed/heterogeneous hardware)
Honors
- NSF CAREER Award
Research Honors
- Honorable Mention of the ICLR 2024 Outstanding Paper Awards (2024)
- OOPSLA Distinguished Artifact Award (2015)
- OOPSLA Distinguished Paper Award (2015)
Recent Courses Taught
- CS 498 LS3 (CS 498 LSG, CS 498 LSU) - Machine Learning System
- CS 598 AIE - AI Efficiency: Sys. & Algor.
News Notes
- 12/1/2025
CS assistant professor Minjia Zhang's group won a Best Student Paper Award at SC'25. The paper: X-MoE: Enabling Scalable Training for Emerging Mixture-of-Experts Architectures on HPC Platforms by Yueming Yuan, Ahan Gupta, Jianping Li and Minjia Zhang from the University of Illinois Urbana-Champaign, along with Sajal Dash and Feiyi Wang from the Oak Ridge National Laboratory.
- 9/8/2025
CS assistant professor Minjia Zhang has been selected for funding through the Spring 2025 Build on Trainium Amazon Research Awards (ARA) for “Trainium-native MoE: Developing kernel and system optimizations for efficient and scalable MoE training” and will be awarded $250K in Amazon Web Services (AWS) credits.