About Me
I am a final-year Ph.D. candidate in Computer Science at Georgia Institute of Technology, working at SSLAB coadvised by Taesoo Kim and Anand Iyer. Before Georgia Tech, I graduated from The Chinese University of Hong Kong with a Bachelor's degree in Computer Science. My research interests include systems for deep graph learning and general machine learning. I am currectly exploring systems aspects of training/serving dynamic GNNs and Graph-based RAG for LLMs.
Education
Ph.D in Computer Science
Georgia Institute of Technology
Advisors: Taesoo Kim, Anand Iyer
Aug. 2019-present
B.S. in Computer Science with Honours, First Class
The Chinese University of Hong Kong (CUHK)*
Advisor: James Cheng
*A joint program offered by Sun Yat-Sen University and CUHK.
Aug. 2015-May. 2019
Experience
Software Engineer Intern
Meta Platforms Inc., Menlo Park, CA
May. 2025-Aug. 2025
Research Intern
Microsoft Research, Redmond, WA
May. 2022-Aug. 2022
Publications and Preprints
Principles and Methodologies for Serial Performance Optimization (to appear)
Heterogeneous Graph Neural Network on Semantic Tree [paper]
ReInc: Scaling Training of Dynamic Graph Neural Networks [paper]
Improving DNN Inference Throughput Using Practical, Per-Input Compute Adaptation [paper]
DynaGraph: Dynamic Graph Neural Networks at Scale [paper]
Sujin Park, Mingyu Guan, Xiang Cheng, Taesoo Kim
Proceedings of the 19th USENIX Symposium on Operating Systems Design and Implementation (OSDI)
Boston, MA, USA, Jul 2025
Mingyu Guan, Jack W. Stokes, Qinlong Luo, Fuchen Liu, Purvanshi Mehta, Elnaz Nouri, Taesoo Kim
Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence
Philadelphia, PA, USA, Feb 2025
Mingyu Guan, Saumia Singhal, Taesoo Kim, and Anand Padmanabha Iyer
arXiv preprint
arXiv:2501.15348, Jan 2025
Anand Iyer, Mingyu Guan, Yinwei Dai, Rui Pan, Swapnil Gandhi, Ravi Netravali
In Proceedings of the 30th Symposium on Operating Systems Principles (SOSP)
Austin, TX, USA, Nov 2024
Mingyu Guan, Anand Padmanabha Iyer, Taesoo Kim
In Proceedings of the 5th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA) (GRADES-NDA)
Philadelphia, PA, USA, June 2022
Talks
TAITEE: Bridging the Trust Gap From Claims to Proof in AI Model Training [session]
Confidential Computing Summit ,San Francisco, CA, USA, Jun 2025
Services
Artifact Evaluation Committee, The 30th Symposium on Operating Systems Principles (SOSP '24).
External Review Committee, 2024 USENIX Annual Technical Conference (ATC '24).