Fang-Yi Yu

    I am a postdoctoral fellow at Harvard John A. Paulson School of Engineering and Applied Sciences hosted by Yiling Chen.

    I received my Ph.D. degree in ​ Computer Science and Engineering Division from the University of Michigan advised by Grant Schoenebeck.

    I am on the academic job market. Please reach out to me if you are hiring!

    Research Interests

    Machine Learning with strategic agents, economics and computation, and theoretical computer science

    Maniscript

    1. Optimal Scoring Rule Design
      Yiling Chen, Fang-Yi Yu.

    Peer-reviewed papers

    1. Optimal Local Bayesian Differential Privacy over Markov Chains
      Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu.
      The 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022).

    2. Subspace Differential Privacy
      Jie Gao, Ruobin Gong, Fang-Yi Yu.
      The 36th International Conference on Artificial Intelligence (AAAI 2022).

    3. The Limits of Multi-task Peer Prediction
      Shuran Zheng, Fang-Yi Yu, Yiling Chen.
      The 22th ACM Conference on Economics and Computation (EC 2021).

    4. ​Cooperation in Threshold Public Projects with Binary Actions
      Yiling Chen, Biaoshuai Tao, Fang-Yi Yu.
      The 30th International Joint Conference on Artificial Intelligence (IJCAI 2021).

    5. Information Elicitation from Rowdy Crowds
      Grant Schoenebeck, Fang-Yi Yu, Yichi Zhang.
      The 30th Web Conference (WWW 2021).

    6. Timely Information from Prediction Markets
      Grant Schoenebeck, Chenkai Yu, Fang-Yi Yu.
      The 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021).

    7. Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach
      Grant Schoenebeck, Fang-Yi Yu.
      The 12th Innovations in Theoretical Computer Science Conference (ITCS 2021). [poster]

    8. Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question
      Grant Schoenebeck, Fang-Yi Yu.
      The 16th International Conference on Web and Internet Economics (WINE 2020). [slides, poster, video]

    9. Escaping Saddle Points in Constant Dimensional Spaces: an Agent-based Modeling Perspective
      Grant Schoenebeck, Fang-Yi Yu.
      The 21st ACM Conference on Economics and Computation (EC 2020). [slides, short slides, poster, video]

    10. Limitations of Greed: Influence Maximization in Undirected Networks Re-visited
      Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu.
      The 19th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2020).

    11. Information Elicitation Mechanisms for Statistical Estimation
      Yuqing Kong, Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu.
      The 34th International Conference on Artificial Intelligence (AAAI 2020). [poster]

    12. Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization​​​
      Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu.
      The 23th International Conference on Randomization and Computation (RANDOM 2019). [slides]

    13. The Volatility of Weak Ties: Co-evolution of Selection and Influence in Social Networks
      Jie Gao, Grant Schoenebeck, Fang-Yi Yu.
      The 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019). [slides]

    14. Consensus of Interacting Particle Systems on Erdös-Rényi Graphs
      Grant Schoenebeck, Fang-Yi Yu.
      The 29th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2018). [slides]

    15. Cascades and Myopic Routing in Nonhomogeneous Kleinberg’s Small World Model
      Jie Gao, Grant Schoenebeck, Fang-Yi Yu.
      The 13th International Conference on Web and Internet Economics (WINE 2017). [slides]

    16. Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents
      Jie Gao, Bo Li, Grant Schoenebeck, Fang-Yi Yu.
      The 30th International Conference on Artificial Intelligence (AAAI 2017). [slides]

    17. Complex Contagions on Configuration Model Graphs with a Power-Law Degree Distribution
      Grant Schoenebeck, Fang-Yi Yu.
      The 12th Conference on Web and Internet Economics (WINE 2016). [slides]

    18. Sybil Detection Using Latent Network Structure
      Aaron Snook, Grant Schoenebeck, Fang-Yi Yu.
      The 17th ACM Conference on Economics and Computation (EC 2016). [slides]

    19. General Threshold Model for Social Cascades: Analysis and Simulations
      Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck, Fang-Yi Yu.
      The 17th ACM Conference on Economics and Computation (EC 2016). [slides]