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
- SMILE Lab, NEU, Boston, U.S. Sep 2021- Now
Research Assistant to Prof. Yun Raymond Fu, working on anomly detection and optimization - Adobe Research, San Jose, U.S. May 2024 - Now
AI/ML Intern - GenAI Research, mentored by Dr. Lingzhi Zhang, Dr. Qing Liu, Dr. Mang tik Chiu, Dr. Connelly Barnes, Dr. Yuqian Zhou, Dr. Sohrab Amirghodsi, Dr. Eli Shechtman and Dr. Zhe Lin - Adobe Research, San Jose, U.S. May 2023 - Dec 2023
Research Intern, mentored by Dr. Gang Wu, Dr. Ruiyi Zhang, Dr. Haoliang Wang and Dr. Uttaran Bhattacharya - 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
- Efficient Reasoning with Hidden Thinking
Xuan Shen, Yizhou Wang, Xiangxi Shi, Yanzhi Wang, Pu Zhao, Jiuxiang Gu
[arXiv, Code] - 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
(Oral, top 8%) IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025
[Paper, Project, Video] - 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
(Spotlight) NeurIPS 2019 Optimization Foundations for Reinforcement Learning Workshop
[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)
[Paper, Code] - 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
[Paper] - Self-Directed Online Machine Learning for Topology Optimization
Changyu Deng, Yizhou Wang, Can Qin, Yun Fu and Wei Lu
Nature Communications (NC), 2022
[arXiv, Paper, Website, Tech Xplore News, Code]
Book Chapter
- Human Activity Recognition and Anomaly Detection—4th International Workshop, DL-HAR 2024, and First International Workshop, ADFM 2024, Held in Conjunction with IJCAI 2024, Jeju, South Korea, August 3–9, 2024, Revised Selected Papers
Kuan-Chuan Peng, Yizhou Wang, Ziyue Li, Zhenghua Chen, Jianfei Yang, Sungho Suh, Min Wu
Part of the book series: Communications in Computer and Information Science (CCIS, volume 2201)
Included in the following conference series:
IJCAI: International Joint Conference on Artificial Intelligence
Conference proceedings info: IJCAI 2024.
[Book]
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
Conference Reviewer
- ICML 2022, 2023, 2024, 2025
- NeurIPS 2021, 2022, 2023, 2024, 2025
- ICLR 2022, 2024, 2025
- CVPR 2022, 2023, 2024, 2025
- ICCV 2023, 2025
- ECCV 2022, 2024
- KDD 2023
- AISTATS 2025
- AAAI 2023
- IJCAI 2023, 2024
- SDM 2024
- PAKDD 2023
- ICME 2022
- ACCV 2024
- CVPR Workshop on Fair, Data-efficient, and Trusted Computer Vision, 2024, 2025
- CVPR Workshop on Multimodal Algorithmic Reasoning, 2024
- ICCV Workshop on Analysis and Modeling of Faces and Gestures, 2023
- ECCV Workshop on Unlearning and Model Editing, 2024
- ECCV Workshop on Vision With Biased or Scarce Data, 2022
- AAAI Workshop on Scalable and Efficient Artificial Intelligence Systems, 2025
- AAAI Workshop on Artificial Intelligence with Biased or Scarse Data, 2024
Journal Reviewer
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- International Journal of Computer Vision (IJCV)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- Pattern Recognition (PR)
- ACM Transactions on Knowledge Discovery from Data (TKDD)
- IEEE Internet of Things Journal (IoT)
- Knowledge and Information Systems (KAIS)
- Journal of Big Data
- 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 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