Professional Summary
About Me
Juntao Zhao is a PhD Candidate at the University of Hong Kong. His research focuses on machine learning systems (Mlsys), with a specific emphasis on efficient inference and training of large foundation models (LFM), including vision-language models (VLM) and large language models (LLM), as well as quantization techniques. He also has a solid background in games and blockchain.
Education
PhD in Machine Learning System
University of Hong Kong
BSc Computer Science And Technology
The Chinese University of Hong Kong (shenzhen)
Interests
Machine Learning System
Games
Blockchain
Recent Publications
(2026).
Efficient LLM Serving on Hybrid Real-time and Best-effort Requests.
IEEE INFOCOM 2026.
(2026).
MegaScale-Data: Scaling DataLoader for Multisource Large Foundation Model Training.
EuroSys 2026.
(2025).
SplitQuant: Resource-Efficient LLM Offline Serving on Heterogeneous GPUs via Phase-Aware Model Partition and Adaptive Quantization.
PPoPP 2024 Poster; IEEE Cluster 2025.
(2024).
Cdmpp: A device-model agnostic framework for latency prediction of tensor programs.
Proceedings of the Nineteenth European Conference on Computer Systems.