Biography of Xiaoqi Tan

Dr. Xiaoqi Tan is an Assistant Professor in the Department of Computing Science at the University of Alberta and a Fellow of Alberta Machine Intelligence Institute (Amii). Prior to joining the University of Alberta in July 2021, he was a Postdoctoral Fellow at the University of Toronto. He received his Ph.D. from the Hong Kong University of Science and Technology (HKUST) in 2018. During his Ph.D., he was also a visiting research fellow at the School of Engineering and Applied Sciences, Harvard University.

Dr. Tan’s research focuses on algorithms and decision-making under uncertainty, especially online algorithms, economic aspects of algorithms, and learning based on different forms of information access. He leads the System-driven Optimization & Decision Algorithms Lab (SODALab) at the University of Alberta. His work has been supported by NSERC Discovery Grants, NSERC Alliance Grants, Alberta Machine Intelligence Institute (Amii) as part of the Pan-Canadian Artificial Intelligence Strategy, Alberta Innovates, and Alberta’s Major Innovation Fund.

Dr. Tan has served on the program committees of multiple leading conferences, including ACM SIGMETRICS, WINE, and ACM e-Energy. He is also a frequent reviewer for major conferences on AI/ML, TCS, and EconCS, such as AAAI, ICML, IJCAI, NeurIPS, RANDOM, SODA, and WWW (listed in alphabetical order). In addition, he has reviewed for leading journals in AI/ML, operations research, and IEEE/ACM, including Journal of Artificial Intelligence Research, Operations Research, Management Science, Performance Evaluation, and various IEEE/ACM Transactions. Dr. Tan has also contributed to national and international grant review processes, including those for MITACS, the Dutch Research Council, and the Hong Kong Research Grants Council.


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