Hanrui Zhang

Contact: hanruiz1 at cs dot cmu dot edu (please use this one for review requests, etc.), or hanrui at cmu dot edu

I am a final-year PhD student in Computer Science at Carnegie Mellon University, advised by Vincent Conitzer. I did my undergraduate in Yao Class, Tsinghua University, where I worked closely with Pingzhong Tang. From September 2016 to May 2017, I interned at MSR Asia in Beijing, where I was hosted by Wei Chen. In Summer 2021, I interned at Google, where I worked closely with Benjamin Miller, Renato Paes Leme, and Jon Schneider. During Summer 2022, I was a student researcher at Google, where I worked closely with Yuan Deng, Mohammad Mahdian, Jieming Mao, Vahab Mirrokni, and Song Zuo.

I am interested in Economics and Computation -- problems with economic motivations that can be approached using techniques from computer science. My recent research focuses on learning and decision making in complex environments, in the presence of strategic behavior, with limited means of interaction, under uncertainty of the future. One particular topic of interest is machine learning in the presence of strategic manipulation.

I am on the 2022-2023 academic job market. A short version of my research statement can be found here.

Publications and (Some) Manuscripts

*: alphabetical order
  1. Efficiency of the First-Price Auction in the Autobidding World. [arXiv]
    Yuan Deng*, Jieming Mao*, Vahab Mirrokni*, Hanrui Zhang*, Song Zuo*.
    Manuscript.

  2. Truthful Stochastic Probing: Auctions Meet Information Retrieval. [pdf]
    Gagan Goel*, Renato Paes Leme*, Jon Schneider*, David Thompson*, Hanrui Zhang*.
    Manuscript.

  3. Nonbossy Mechanisms: Mechanism Design with Almost-Vanishing Externalities. [pdf]
    Renato Paes Leme*, Jon Schneider*, Hanrui Zhang*.
    Manuscript.

  4. Posted Pricing and Dynamic Prior-independent Mechanisms with Value Maximizers. [pdf]
    Yuan Deng*, Vahab Mirrokni*, Hanrui Zhang*.
    36th Conference on Neural Information Processing Systems (NeurIPS 2022).

  5. Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design. [arXiv]
    Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah.
    10th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2022).

  6. Efficient Algorithms for Planning with Participation Constraints. [pdf] [arXiv]
    Hanrui Zhang, Yu Cheng, Vincent Conitzer.
    Twenty-Third ACM Conference on Economics and Computation (EC 2022).

  7. Planning with Participation Constraints. [pdf]
    Hanrui Zhang, Yu Cheng, Vincent Conitzer.
    36th AAAI Conference on Artificial Intelligence (AAAI 2022).

  8. Learning Influence Adoption in Heterogeneous Networks. [pdf]
    Vincent Conitzer*, Debmalya Panigrahi*, Hanrui Zhang*.
    36th AAAI Conference on Artificial Intelligence (AAAI 2022).

  9. Automated Dynamic Mechanism Design. [pdf] [arXiv]
    Hanrui Zhang, Vincent Conitzer.
    Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021).

  10. Prior-independent Dynamic Auctions for a Value-maximizing Buyer. [pdf]
    Yuan Deng*, Hanrui Zhang*.
    Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021).

  11. Automated Mechanism Design for Classification with Partial Verification. [pdf]
    Hanrui Zhang, Yu Cheng, Vincent Conitzer.
    Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021).

  12. Incentive-Aware PAC Learning. [pdf]
    Hanrui Zhang, Vincent Conitzer.
    Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021).

  13. Classification with Few Tests through Self-Selection. [pdf]
    Hanrui Zhang, Yu Cheng, Vincent Conitzer.
    Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021).

  14. Classification with Strategically Withheld Data. [arXiv]
    Anilesh Krishnaswamy*, Haoming Li*, David Rein*, Hanrui Zhang*, Vincent Conitzer.
    Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021).

  15. Online Combinatorial Auctions. [pdf]
    Yuan Deng*, Debmalya Panigrahi*, Hanrui Zhang*.
    Thirty-second Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2021).

  16. Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments. [arXiv]
    Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang.
    Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020).

  17. A Generic Truthful Mechanism for Combinatorial Auctions. [pdf]
    Hanrui Zhang.
    16th Conference on Web and Internet Economics (WINE 2020).

  18. Improved Prophet Inequalities for Combinatorial Welfare Maximization with (Approximately) Subadditive Agents. [pdf]
    Hanrui Zhang.
    28th Annual European Symposium on Algorithms (ESA 2020), Best Student Paper.

  19. Learning the Valuations of a $k$-demand Agent. [pdf]
    Hanrui Zhang, Vincent Conitzer.
    Thirty-seventh International Conference on Machine Learning (ICML 2020).

  20. Learning Opinions in Social Networks. [pdf]
    Vincent Conitzer*, Debmalya Panigrahi*, Hanrui Zhang*.
    Thirty-seventh International Conference on Machine Learning (ICML 2020).

  21. Nearly Linear Row Sampling Algorithm for Quantile Regression. [arXiv]
    Yi Li*, Ruosong Wang*, Lin F. Yang*, Hanrui Zhang*.
    Thirty-seventh International Conference on Machine Learning (ICML 2020).

  22. Combinatorial Ski Rental and Online Bipartite Matching. [pdf]
    Hanrui Zhang, Vincent Conitzer.
    Twenty-First ACM Conference on Economics and Computation (EC 2020).

  23. A Graph-Theoretical Basis of Stochastic-Cascading Network Influence: Characterizations of Influence-Based Centrality. [pdf] [arXiv]
    Wei Chen*, Shang-Hua Teng*, Hanrui Zhang*.
    Theoretical Computer Science (TCS).

  24. Distinguishing Distributions When Samples Are Strategically Transformed. [pdf] [poster]
    Hanrui Zhang, Yu Cheng, Vincent Conitzer.
    Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019).

  25. Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle. [arXiv]
    Simon S. Du*, Yuping Luo*, Ruosong Wang*, Hanrui Zhang*.
    Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019).

  26. When Samples Are Strategically Selected. [pdf] [poster]
    Hanrui Zhang, Yu Cheng, Vincent Conitzer.
    Thirty-Sixth International Conference on Machine Learning (ICML 2019).

  27. A PAC Framework for Aggregating Agents' Judgments. [pdf] [poster]
    Hanrui Zhang, Vincent Conitzer.
    Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019).

  28. Learning Set Functions with Limited Complementarity. [pdf] [poster]
    Hanrui Zhang.
    Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019).

  29. A Better Algorithm for Societal Tradeoffs. [pdf] [poster]
    Hanrui Zhang, Yu Cheng, Vincent Conitzer.
    Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019).

  30. Capturing Complementarity in Set Functions by Going Beyond Submodularity/Subadditivity. [pdf] [arXiv]
    Wei Chen*, Shang-Hua Teng*, Hanrui Zhang*.
    10th Innovations in Theoretical Computer Science (ITCS 2019).

  31. An Improved Algorithm for Incremental DFS Tree in Undirected Graphs. [pdf] [arXiv]
    Lijie Chen*, Ran Duan*, Ruosong Wang*, Hanrui Zhang*, Tianyi Zhang*.
    16th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2018).

  32. Approximation-Variance Tradeoffs in Facility Location Games. [pdf]
    Ariel Procaccia*, David Wajc*, Hanrui Zhang*.
    Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018).

  33. Complete Submodularity Characterization in the Comparative Independent Cascade Model. [pdf] [arXiv]
    Wei Chen*, Hanrui Zhang*.
    Theoretical Computer Science (TCS).

  34. Efficient Near-Optimal Algorithms for Barter Exchange. [pdf]
    Zhipeng Jia*, Pingzhong Tang*, Ruosong Wang*, Hanrui Zhang*.
    16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017).

  35. Unit-Sphere Games. [pdf] [arXiv]
    Pingzhong Tang*, Hanrui Zhang*.
    International Journal of Game Theory (IJGT).

Professional Services

Conference Reviewing: AAAI (2020, 2021, 2022, 2023), AAMAS (2020), AISTATS (2019, 2021), EC (2020, 2021, 2022), FOCS (2019), ICALP (2020), ICLR (2022), ICML (2020, 2021, 2022), IJCAI (2021 SPC), ITCS (2022), NeurIPS (2020, 2021, 2022), PODS (2021), SAGT (2022), SoCG (2020), WINE (2016, 2021, 2022), WWW (2021, 2022 PC).

Journal Reviewing: Algorithmica, Games and Economic Behavior, Journal of Machine Learning Research, Operations Research, SIAM Journal on Computing.

Teaching

Last updated: Sep 2022