Yikun Ban

I am a Ph.D. student in computer science at University of Illinois at Urbana-Champaign , advised by Prof. Jingrui He , and I work closely with Prof. Arindam Banerjee and Prof. Hanghang Tong. Prior to this, I obtained my Master degree from EECS, Peking University and bachelor degree from Wuhan University.
I am interetsed in provable algorithms in the space of multi-armed bandits, deep learning theory, and reinforcement learning, to solve real-world exploitation-exploration problems. In the past, my research efforts have included similarity metric, clustering algorithms, and graph mining algorithms with applications in fraud detection.
Google Scholar

  • 2022.09   One paper was accepted by NeurIPS 2022!
  • 2022.05   One paper was accepted by KDD 2022!
  • 2022.01   One paper was accepted by ICLR 2022 Spotlight! EE-Net provides a novel neural-based exploration strategy, distinct from standard UCB and TS.
  • 2021.05   One paper was accepted by KDD 2021!
  • 2021.01   One paper was accepted by WWW 2021!


  1. Yunzhe Qi*, Yikun Ban*, and Jingrui He
    Graph Neural Bandits
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining ( KDD'23 )
    To appear
  2. Yikun Ban*, Yuheng Zhang*, Hanghang Tong, Arindam Banerjee, and Jingrui He (* Equal Contribution)
    Improved Algorithms for Neural Active Learning
    Thirty-sixth Conference on Neural Information Processing Systems ( NeurIPS'22 )
  3. Dongqi Fu, Yikun Ban, Hanghang Tong, Ross Maciejewski, and Jingrui He
    DISCO: Comprehensive and Explainable Disinformation Detection
    ACM International Conference on Information and Knowledge Management (Demo Track) ( CIKM'22 )
  4. Yunzhe Qi, Yikun Ban, and Jingrui He
    Neural Bandit with Arm Group Graph
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining ( KDD'22 )
  5. Yikun Ban, Yuchen Yan, Arindam Banerjee, and Jingrui He
    EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits
    International Conference on Learning Representations ( ICLR'22, Spotlight (176/3391))
  6. Yikun Ban, Jingrui He, and Curtiss B. Cook
    Multi-Facet Contextual Bandits: A Neural Network Perspective
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining ( KDD'21 )
  7. Yikun Ban and Jingrui He
    Local Clustering in Contextual Multi-Armed Bandits
    The Web Conference ( WWW'21 )
  8. Yuchen Yan, Lihui Liu, Yikun Ban, Baoyu Jing, and Hanghang Tong
    Dynamic Knowledge Graph Alignment
    AAAI Conference on Artificial Intelligence ( AAAI'21 )
  9. Yikun Ban and Jingrui He
    Generic Outlier Detection in Multi-Armed Bandit
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining ( KDD'20 )
  10. Yikun Ban, Xin liu, Ling Huang, Yitao Duan, Xue Liu, and Wei Xu
    No Place to Hide: Catching Fraudulent Entities in Tensors
    The Web Conference ( WWW ’19 )


  • May. 2022 - Aug. 2022, Applied Scientist Intern, AI Platform, Amazon
  • Jan. 2018 - May. 2019, Research Intern, IIIS, Tsinghua University, worked with Prof. Wei Xu, Dr. Ling Huang, and Dr. Yitao Duan.

Selected Awards and Honors

  • 10/2022   NeurIPS 2022 Scholar Award
  • 05/2022   Outstanding ICML'22 Reviewer
  • 08/2020 & 08/2021   KDD’20, KDD’21, Student Travel Award
  • 09/2018   Outstanding Students of Peking University
  • 06/2016   Outstanding Graduate Students of Wuhan University
  • 8/2015   First Prized, The “China Software Cup” Software Design Competition for College Students (Top 0.1%, 2859 teams involved)
  • 11/2014   Second Prized in National Finals, First Prized in Provincial Finals, The “Challenge Cup” China College Student’s Entrepreneurship Competition (Top 0.2%, 5000+ teams involved)


    Sep. 2019 - Present
    Ph.D., Computer Science, University of Illinois at Urbana-Champaign, Illinois, US
    Sep. 2016 - Jul. 2019
    M.S., Computer Science (Architecture), Peking University, Beijing, China
    Sep. 2012 - Jul. 2016
    B.S., Spatial information & Digitalized Technology, Wuhan University, Wuhan, China


  • Program Committee:ICML'22, KDD'22, AAAI'22, KDD'21, IJCAI'21, CIKM'21