Welcome to Zeyi Wen's Homepage

Dr. Zeyi Wen is Assistant Professor at the Data Science and Analytics (DSA) Thrust of Information Hub at Hong Kong University of Science and Technology, Guangzhou (HKUST-GZ). Before joining HKUST-GZ, he was Lecturer at The University of Western Australia (2025 QS World University Rankings 77), Research Fellow at National University of Singapore and The University of Melbourne after PhD completion at The University of Melbourne. He obtained his Bachelor's Degree from South China University of Technology. Dr. Wen was a winner of Best Paper Award at IEEE Transactions on Parallel and Distributed Systems (TPDS) 2019. His research work has led to open-source ML systems including ThunderGBM Star and ThunderSVM Star. He is an Action Editor (AE) of MLOSS section for the Journal of Machine Learning Research (JMLR).

Jun 2025: Three papers accepted by ICPP'25, ACM TKDD, and Pattern Recognition (PR), respectively.
Jan 2025: A paper on small language models was accpeted by NAACL'25.
Dec 2024: Two papers on LLM inference and fine-tuning got accepted by AAAI'25.
Nov 2024: Our paper on GBDTs for High Dimensional Data was accepted by KDD'25.
Sep 2024: Our paper on SVMs for ABSA tasks was accepted by EMNLP'24 Findings.
Jun 2024: Our paper on Bayesian Network Learning was accepted by IEEE TPDS.
May 2024: Our paper on PGM inference acceleration was accepted by USENIX ATC'24.

Large Language Model Inference/Training/Fine-Tuning Acceleration
Machine Learning Systems, Automatic Machine Learning, and High-Performance Computing

Current Courses at HKUST-GZ

Past Courses at UWA

My graduate students and their research

Name	Research
Hangyu Yang (PhD student to start from Spring 2026)	Offloading for LLMs
Guang Huang (PhD student to start from Fall 2025)	KV cache optimization
Fan Zhang (PhD student to start from Fall 2025)	LLM inference optimization
Guoli Wu (PhD student from Spring 2025)	LLM inference optimization
Haichao Fang (RBM MPhil student from Fall 2024)	LLMs for health applications
Chengxi Liao (PhD student since Fall 2024)	Long context LLM inference
Tong Yuan (PhD student since Fall 2024)	Speculative Decoding System
Ruijia Yang (PhD student since Fall 2024)	Efficient LLM training
Rui Zhang (PhD student since Fall 2024)	Accelerating kernel machine training
Zeyuan Lin (Visiting MPhil student from Fall 2024)	Kernels for CNNs
Xinhao Huang (PhD student from Spring 2024)	Model decomposition
Jihang Li (PhD student since Fall 2023)	Learning operator acceleration with GPUs
Minping Chen (PhD student since Fall 2023)	Efficient fine-tuning for LLMs
Yuebin Xu (PhD student since Fall 2023)	Hyper-parameter optimization (HPO) for LLMs
Xuemei Peng (PhD student since Spring 2023)	Efficient LLM serving
Yile Chen (Visiting PhD student since 2022)	Hyper-parameter optimization (HPO)
Hanfeng Liu (PhD student since Fall 2022)	Parallel GBDT training

My graduated students

Name	Employment	Research
Youliang Huang (Master at HKUST-GZ, 2023-25)	PhD at Boston University	Efficient fine-tuning for LLMs
Jiyuan Shi (Master at HKUST-GZ, 2023-25)	ML Engineer at WeChat, Tencent	LLM compression
Tong Yuan (Master at HKUST-GZ, 2022-24)	PhD at HKUST-GZ	Structure learning efficiency optimization
Yawen Chen (PhD at SCUT, 2020-24)	Lecturer at Henan University	Kernel machine optimization and their applications
Jiantong Jiang (PhD at UWA, 2021-24)	Postdoc at Melbourne University	Graphical model efficiency optimization
Peiyu Yang (PhD at UWA, 2021-24)	Postdoc at Melbourne University	Explaining deep neural networks

2025: ICPP, SC, NeurIPS, ICML, KDD, ICLR, ICDE, AAAI, ACL ARR, DASFAA (demo track co-chair)
2024: KDD, NeurIPS, AAAI, CIKM, EDBT, EMNLP
2023: KDD, SC, AAAI, CIKM, WSDM, SIGIR, ECML-PKDD, CCGrid,
2022: KDD, SC, AAAI, SIGIR, WSDM, CIKM, CVPR, ECCV