Kaiqiang Xu

Research

My research focuses on improving the efficiency and accessibility of machine learning systems and AI computing infrastructure. A core theme of my work is designing new abstractions, parallelization strategies, and scheduling algorithms that exploit the unique characteristics of machine learning workloads and large-scale clusters.

I am currently in the final year of my PhD in Computer Science at HKUST, advised by Prof. Kai Chen. During my time at HKUST, I led the design and development of TACC, an AI cluster that supports over 600 university members. I earned my BSc in Computer Science from Renmin University of China.

My work has been published in top-tier conferences across computer networks, operating systems, architecture, and databases, including NSDI, OSDI, ASPLOS, and SIGMOD. I was also a researcher at Google, where I work on efficient infrastructure and frameworks for large models.

Selected Papers (Full publication list and Google Scholar)

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GREEN: Carbon-efficient Resource Scheduling for Machine Learning Clusters

Kaiqiang Xu, Decang Sun, Han Tian, Junxue Zhang, Kai Chen

NSDI '25 USENIX Symposium on Networked Systems Design and Implementation

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Design and Operation of Shared Machine Learning Clusters on Campus

Kaiqiang Xu, Decang Sun, Hao Wang, Zhenghang Ren, Xinchen Wan, Xudong Liao, Zilong Wang, Junxue Zhang, Kai Chen

ASPLOS '25 ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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Sequoia: An Accessible and Extensible Framework for Privacy-Preserving Machine Learning over Distributed Data

Kaiqiang Xu, Di Chai, Junxue Zhang, Fan Lai, Kai Chen

SIGMOD '25 ACM International Conference on Management of Data

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Enabling Efficient GPU Communication over Multiple NICs with FuseLink

Zhenghang Ren, Yuxuan Li, Zilong Wang, Xinyang Huang, Wenxue Li, Kaiqiang Xu, Xudong Liao, Yijun Sun, Bowen Liu, Han Tian, Junxue Zhang, Mingfei Wang, Zhizhen Zhong, Guyue Liu, Ying Zhang, Kai Chen

OSDI '25 USENIX Symposium on Operating Systems Design and Implementation