Hongao Wang (王弘奥)
Hongao Wang (王弘奥)

PhD candidate

About me

My name is Hongao Wang (王弘奥). I am a PhD student at Purdue University since 2021 fall and I am very fortunate to be advised by Prof. Paul Valiant and Prof. Steve Hanneke.

I was a project officer at Nanyang Technological University, which is a position similar to the research assistant in US. It is my honor to be supervised by Prof. Xiaohui Bei at NTU, Singapore. Before that, I was an undergraduate at Shanghai Jiao Tong University and did several research projects with Prof. Nick Gravin from Shanghai University of Finance and Economics.

My research interests include Algorithmic Mechanism Design, Fair Division, Online Algorithm, sublinear algorithm on big data and related statistics and learnability problem on online learning. I am now focusing more on statistics related algorithms and learning theory, even though I did some works on mechanism design and fair division, which I will try to keep working on. I also have broad interests in Theoretical Computer Science.

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Interests
  • Sublinear Algorithms on Big Data and Related Statistics
  • Learning Theory
  • Algorithmic Mechanism Design
  • Fair Division
  • Online Algorithm
Education
  • BSE in Information Engineering, 2014 - 2018

    Shanghai Jiao Tong University

  • PhD in Computer Science, 2021 - present

    Purdue University

Recent Publications
(2026). New Bounds for Circular Trace Reconstruction. 17th Innovations in Theoretical Computer Science Conference (ITCS 2026).
(2025). A Bicriterion Concentration Inequality and Prophet Inequalities for k-Fold Matroid Unions. 16th Innovations in Theoretical Computer Science Conference (ITCS 2025).
(2025). For Universal Multiclass Online Learning, Bandit Feedback and Full Supervision are Equivalent. 36th International Conference on Algorithmic Learning Theory.
(2025). Non-Uniform Multiclass Learning with Bandit Feedback. The Thirty-ninth Annual Conference on Neural Information Processing Systems.
(2024). A Theory of Optimistically Universal Online Learnability for General Concept Classes. The Thirty-eighth Annual Conference on Neural Information Processing Systems.