Zhixuan Fang ()


Assistant Professor,
Institute for Interdisciplinary Information Sciences (IIIS),
Tsinghua University
Beijing, China
zfang [AT] mail.tsinghua.edu.cn

About me

I am now a tenure-track assistant Professor in the Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University.

I received my PhD degree from IIIS, Tsinghua University in 2018 (supervised by Prof. Andrew Chi-Chih Yao and Prof. Longbo Huang). I was then a postdoctoral researcher in the Department of Infomation Engineering, The Chinse University of Hong Kong, advised by Prof. Jianwei Huang. Prior to my Ph.D., I received my B.S. degree in School of Physics, Peking University in 2013.

I am looking for motivated PhD, postdoc, and undergrad students. Feel free to contact me if you are interested.


My research focuses on developing methods and solutions to address challenges in multi-agent systems consist of interest-driven individuals. Specifically, my recent studies are mostly on the topics of online platforms and blockchain systems. I model and analyze the systems through the lens of mechanism design, mathematics optimization, economics, and algorithms.

Academic experiences

  • Visiting scholar, EECS@UC Berkeley. Hosted by Prof. Jean Walrand, Aug. 2016 - Dec. 2016.

  • Visit Department of Computing and Mathematical Sciences (CMS) @ Caltech. Hosted by Prof. Adam Wierman, Nov. 2016

Recent highlights

  1. Zhixuan Fang and Jianwei Huang, “When Reputation Meets Subsidy: How to Build High Quality On Demand Service Platforms,” Proceedings of IEEE International Conference on Computer Communications (INFOCOM), 2020.

  2. Ningning Ding, Zhixuan Fang and Jianwei Huang, “Incentive Mechanism Design for Federated Learning with Multi-Dimensional Private Information,” Proceedings of the 18th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), 2020.

  3. Yunshu Liu, Zhixuan Fang, Man Hon Cheung, Wei Cai and Jianwei Huang, “Economics of Blockchain Storage,” Proceedings of IEEE International Conference on Communications (ICC), 2020.

  4. Ling Pan, Qingpeng Cai, Zhixuan Fang, Pingzhong Tang, and Longbo Huang, “A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems,” Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), 2019.

  5. Zhixuan Fang, Longbo Huang and Adam Wierman, “Loyalty Programs in the Sharing Economy: Optimality and Competition,” Proceedings of the 19th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2018.

  6. Zhixuan Fang, Longbo Huang and Adam Wierman, “Prices and Subsidies in the Sharing Economy,” Proceedings of the International Conference on World Wide Web (WWW), 2017.