About Me

I am a 5th-year Ph.D. candidate in Computer Engineering at Northeastern Unversity (NEU). I am supervised by Prof. Yun Raymond Fu and I am a member of SmileLab. My research mainly focuses on LLM, Multimodal LLM and anomaly detection

My ultimate goal of AI related research is to reach AI consciousness safely, which might help human beings escape the earth and explore the universe.

Education

  • Northeastern University (NEU) 2020-
    Ph.D. in Computer Engineering
    Supervisor: Prof. Yun Raymond Fu
  • Northeastern University (NEU) 2020-2023
    M.S. in Elctrical Engineering
    Concentration: Computer Vision Mach Learn&Alg
  • Xi’an Jiaotong University (XJTU) 2016-2020
    B.S. in Mathematics and Applied Mathematics (National Honors Program)
    GPA: 91.17/100 (3.85/4.00)
  • Georgia Institute of Technology (GaTech) 2019 Spring
    Georgia Tech School of Mathematics Visiting Honors Student Program
  • Peking University (PKU) 2018 Summer
    DeeCamp Member, mentored by Megvii
  • University of Alberta 2017 Summer
    International Undergraduate Summer Enrichment Program in Mathematics

Working Experience

Publications

Preprints

  • VaQuitA: Enhancing Alignment in LLM-Assisted Video Understanding
    Yizhou Wang, Ruiyi Zhang, Haoliang Wang, Uttaran Bhattacharya, Yun Fu and Gang Wu
    [arXiv]
  • Explainable Anomaly Detection in Images and Videos: A Survey
    Yizhou Wang, Dongliang Guo (co-first), Sheng Li, Octavia Campus, and Yun Fu
    [arXiv, Code]
  • Rethinking Adam: A Twofold Exponential Moving Average Approach
    Yizhou Wang, Yue Kang, Can Qin, Huan Wang, Yi Xu, Yulun Zhang and Yun Fu
    [arXiv]

Conference Papers

  • Towards Zero-shot 3D Anomaly Localization
    Yizhou Wang, Kuan-Chuan Peng, Yun Fu
    IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025
  • Rewrite the stars
    Xu Ma, Xiyang Dai, Yue Bai, Yizhou Wang, Yun Fu
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
    [Paper, Code]
  • Don’t Judge by the Look: A Motion Coherent Augmentation for Video Recognition
    Yitian Zhang, Yue Bai, Huan Wang, Yizhou Wang, Yun Fu
    International Conference on Learning Representations (ICLR), 2024
    [Paper, Code]
  • Momentum is All You Need for Data-Driven Adaptive Optimization
    Yizhou Wang, Yue Kang (co-first), Can Qin, Huan Wang, Yi Xu, Yulun Zhang and Yun Fu
    IEEE International Conference on Data Mining (ICDM), 2023
    [Paper, Code, Video]
  • Concentric Ring Loss for Face Forgery Detection
    Yu Yin, Yue Bai, Yizhou Wang, and Yun Fu
    IEEE International Conference on Data Mining (ICDM), 2023
    [Paper]
  • Making Reconstruction-based Method Great Again for Video Anomaly Detection
    Yizhou Wang, Can Qin, Yue Bai, Yi Xu, Xu Ma and Yun Fu
    IEEE International Conference on Data Mining (ICDM), 2022
    [arXiv, Code]
  • Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection
    Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai and Yun Fu
    ACM International Conference on Information and Knowledge Management (CIKM), 2022
    [Paper, Code]
  • Robust Semi-supervised Domain Adaptation against Noisy Labels
    Can Qin, Yizhou Wang and Yun Fu
    ACM International Conference on Information and Knowledge Management (CIKM), 2022
    [Paper]
  • MemREIN: Rein the Domain Shift for Cross-Domain Few-Shot Learning
    Yi Xu, Lichen Wang, Yizhou Wang, Can Qin, Yulun Zhang and Yun Fu
    International Joint Conferences on Artificial Intelligence (IJCAI), 2022
    [Paper]
  • Adaptive Trajectory Prediction via Transferable GNN
    Yi Xu, Lichen Wang, Yizhou Wang and Yun Fu
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
    [arXiv]
  • On Computation and Generalization of Generative Adversarial Imitation Learning
    Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang and Tuo Zhao
    International Conference on Learning Representations (ICLR), 2020
    NeurIPS 2019 Optimization Foundations for Reinforcement Learning Workshop (Spotlight)
    [arXiv]

Journal Papers

  • SLA$^2$P: Self-supervised Anomaly Detection with Adversarial Perturbation
    Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai and Yun Fu
    IEEE Transactions on Knowledge and Data Engineering (TKDE) (IF: 8.9)
    [arXiv]
  • An unrolled Implicit Regularization Network for Joint Image and Sensitivity Estimation in Parallel MR Imaging with Convergence Guarantee
    Yan Yang, Yizhou Wang (co-first), Jiazhen Wang, Jian Sun and Zongben Xu
    SIAM Journal on Imaging Sciences (SIIMS), 2023 (IF: 1.938) [Paper]
  • Self-Directed Online Machine Learning for Topology Optimization
    Changyu Deng, Yizhou Wang, Can Qin, Yun Fu and Wei Lu
    Nature Communications (NC), 2022 (IF: 14.919)
    [arXiv, Paper, Website, Tech Xplore News, Code]

Selected Presentations

Selected Awards

  • SDM Doctoral Forum Travel Award, 2024
  • IEEE ICDM Student Travel Award, 2022
  • SIGIR Student Travel Grant, 2022
  • Dean’s Fellowship of Northeastern University, 2020
  • Outstanding graduate of XJTU, 2020
  • National Zhufeng 1st Scholarship (Pilot Scheme of Top-notch Talent Cultivation in Basic Disciplines), 2019
  • Special Prize in 2018 National English Competition for College Students (Top 0.1%), 2018
  • XJTU Pengkang Scholarship (Top 1.5%), 2018
  • National Endeavor Scholarship (Top 2%), 2017

Academic Service

Conference Session Chair

  • SIAM International Conference on Data Mining (SDM), 2024: Session 10 (Text, Web, Social Media)

Workshop Organization

Conference Reviewer

  • ICML 2022, 2023, 2024
  • NeurIPS 2021, 2022, 2023
  • ICLR 2022, 2024, 2025
  • CVPR 2022, 2023, 2024
  • ICCV 2023
  • ECCV 2022, 2024
  • KDD 2023
  • AISTATS 2025
  • AAAI 2023
  • IJCAI 2023, 2024
  • SDM 2024
  • PAKDD 2023
  • ICME 2022
  • ACCV 2024
  • ECCV Workshop on Unlearning and Model Editing, 2024
  • CVPR Workshop on Fair, Data-efficient, and Trusted Computer Vision, 2024
  • CVPR Workshop on Multimodal Algorithmic Reasoning, 2024
  • ICCV Workshop on Analysis and Modeling of Faces and Gestures, 2023
  • ECCV Workshop on Vision With Biased or Scarce Data, 2022
  • AAAI Workshop on Artificial Intelligence with Biased or Scarse Data, 2024

Journal Reviewer

Teaching Experience

Teaching Assistant (TA)

  • EECE 7398 ST: Advances in Deep Learning, Fall 2024
  • EECE 5642: Data Visualization, Northeastern University, Spring 2023 and Spring 2024
  • DS 5230: Unsupervised Machine Learning, Northeastern University, Fall 2023

Contact

Email: wyzjack990122 (at) gmail (dot) com / wang.yizhou (at) northeastern (dot) edu