I am a fourth-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 anomaly detection in machine learning and deep learning. I am also interested in Large Language Models recently.

My ultimate goal of AI related research is to reach the goal of AGI (Artificial General Intelligence), a.k.a., strong AI.

News

• 04/2024: Kuan-Chuan Peng and I are organizing the Workshop on Anomaly Detection with Foundation Models in conjunction with IJCAI 2024! Please consider submitting your relevant works and join us.
• 03/2024: We released a GitHub repository on Explainable Anomaly Detection in Images and Videos: A Survey. Welcome to use and star!
• 02/2024: Our paper on fundamental DNN network design is accepted by CVPR 2024.
• 01/2024: Our paper on data augmentation for video recognition is accepted by ICLR 2024.
• 09/2023: Our papers on adaptive optimizer design and face forgery detection are accepted by ICDM 2023.
• 08/2023: I get Master Degree in ECE from Northeastern University!
• 05/2023: Our paper on parallel MR Imaging is accepted by SIAM Journal on Image Sciences.
• 04/2023: We released a GitHub repository summarizing the SOTA methods and the related papers on 3D anomaly detection. Welcome to use and star!
• 12/2022: I successfully passed the qualifying exam and become a Ph.D. candidate.
• 08/2022: Our paper on video anomaly detection is accepted by ICDM 2022.
• 08/2022: Our papers on unsupervised anomaly detection and semi-supervised domain adaptation are accepted by CIKM 2022.
• 04/2022: Our paper on cross-domain few-shot learning is accepted by IJCAI 2022.
• 03/2022: Our paper on trajectory prediction is accepted by CVPR 2022.
• 12/2021: Our paper on gradient-free topology optimization is accepted by Nature Communications.
• 09/2021: Start the journey at NEU, Boston, MA, after one-year remote study (due to Covid-19 and travel ban).

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

• SMILE Lab, NEU, Boston, U.S. Sep 2021-
  Research Assistant to Prof. Yun Raymond Fu, working on anomly detection and optimization
• Adobe Research, San Jose, U.S. May 2023 - Dec 2023
  Research Intern, mentored by Dr. Gang Wu, Dr. Ruiyi Zhang and Dr. Haoliang Wang
• Mitsubishi Electric Research Laboratories (MERL), Cambridge, U.S. May 2022 - Sep 2022
  Research Intern, mentored by Dr. Kuan-Chuan Peng
• Imagine Lab, XJTU, Xi’an, China Jun 2020 - Aug 2020
  Research Assistant to Prof. Jian Sun, working on deep unfolded iterative algorithm for medical images
• FLASH Lab, GaTech, Atlanta, U.S. Jan 2019 - May 2019
  Research Assistant to Prof. Tuo Zhao, working on generative adversarial imitation learning

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]
• SLA$^2$P: Self-supervised Anomaly Detection with Adversarial Perturbation
  Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai and Yun Fu
  Major revision at IEEE Transactions on Knowledge and Data Engineering (TKDE) (IF: 8.9)
  [arXiv]
• Rethinking Adam: A Twofold Exponential Moving Average Approach
  Yizhou Wang, Yue Kang, Can Qin, Huan Wang, Yi Xu, Yulun Zhang and Yun Fu
  [arXiv]

Journal Papers

• 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]

Conference Papers

• 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]

Selected Presentations

• Oral report at CAS SIAM, Online, 2023
• Oral report at AI2healthcare Talk Video, Online, 2023
• Oral presentation at New England Computer Vision Workshop, MIT, Boston, MA, 2022

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

• the Workshop on Anomaly Detection with Foundation Models in conjunction with IJCAI 2024

Conference Reviewer

• International Conference on Machine Learning (ICML), 2022, 2023, 2024
• Neural Information Processing Systems (NeurIPS), 2021, 2022, 2023
• International Conference on Learning Representations (ICLR), 2022, 2024
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, 2023, 2024
• International Conference on Computer Vision (ICCV), 2023
• European Conference on Computer Vision (ECCV), 2022, 2024
• SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
• AAAI Conference on Artificial Intelligence (AAAI), 2023
• International Joint Conference on Artificial Intelligence (IJCAI), 2023, 2024
• SIAM International Conference on Data Mining (SDM), 2024
• Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2023
• IEEE International Conference on Multimedia and Expo (ICME), 2022
• The 17th Asian Conference on Computer Vision (ACCV), 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

• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
• ACM Transactions on Knowledge Discovery from Data (TKDD)
• Knowledge and Information Systems (KAIS)
• International Journal of Fuzzy Systems (IJFS)
• IEEE Transactions on Intelligent Vehicles (IEEE Trans. Veh. Technol.)
• IEEE Computational Intelligence Magazine (CIM)

Teaching Experience

Teaching Assistant (TA)

• EECE 5642: Data Visualization, Northeastern University, Spring 2023 and Spring 2024
• DS 5230: Unsupervised Machine Learning, Northeastern University, Fall 2023

Miscellaneous

• I am a sports fan. I like basketball (I can dunk 2.95m basketball hoop), soccer, badminton, table tennis and Go chess (I am Amateur 2 Dan). My favorite basketball players are Lebron James and Luka Doncic. My favorite soccer player is Lionel Messi. If you want to play basketball with me, contact me via email or WeChat (see Contact section below). My lab colleagues and I usually play at the second floor of Marino Recreation Center.
• I am a music fan. I love listening to Hiphop. My favorite rappers are 8aceMak1r (a.k.a. PG One) and Post Malone (if he is). I also like singing songs when I have time. Here is my “We Sing” (全民K歌) account where I record my singings. I am actually pretty good at singing as I can easily get SSS scores on “We Sing”.

Contact

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