About me
I received my PhD in Computer Science from the University of Wisconsin–Madison, advised by Prof. Pedro Morgado. I obtained my Master’s degree in Electrical Engineering from Caltech, advised by Prof. Yisong Yue and Prof. Pietro Perona.
I work on self-supervised learning, multimodal retrieval and large vision–language models, with an emphasis on representation learning at different level from semantics to localized, fine-grained, compositional feature for image/video/VLM.
News
- Successfully defended my Ph.D. dissertation in Computer Sciences at the University of Wisconsin–Madison.
- Our paper on QARE, towards extracting disentangled text-guided image representations, accepted at CVPR Findings 2026.
- Research Scientist Intern at Meta Reality Lab this 2025 winter.
- Our paper on TrackVerse, an object-centric video dataset for SSL, accepted at ICCV 2025.
- ML Research Intern at Adobe Firefly this 2025 summer.
- Our paper on Accelerating the pretraining of vision transformers accepted at NeurIPS 2024.
- Our paper on Latent MIM accepted by ECCV 2024.
Publications
 | Towards Text-Guided Attribute-Disentangled Multimodal Representation LearningYibing Wei, Sudeep Katakol, Manuel Brack, Jinhong Lin, Haoyue Bai, Yu-Teng Li, Richard Zhang, Eli Shechtman, Hareesh Ravi, Ajinkya KaleCVPR Findings, 2026 |
 | TrackVerse: A Large-Scale Object-Centric Video Dataset for Image-Level Representation LearningYibing Wei, Samuel Church, Victor Suciu, Jinhong Lin, Cheng-En Wu, Pedro MorgadoICCV, 2025 |
 | Towards Latent Masked Image Modeling for Self-Supervised Visual Representation LearningYibing Wei, Abhinav Gupta, Pedro MorgadoECCV, 2024 |
 | Accelerating Augmentation Invariance PretrainingJinhong Lin,Cheng-En Wu, Yibing Wei, Pedro MorgadoNeurIPS, 2024 |
 | Multispectral Masked Autoencoder for Remote Sensing Representation LearningYibing Wei, Zhicheng Yang, Hang Zhou, Mei Han,Jui-Hsin Lai.NeurIPS, WiML Workshop, 2023 |
 | Dueling Posterior Sampling for Preference-Based Reinforcement LearningEllen Novoseller, Yibing Wei, Yanan Sui, Yisong Yue, and Joel W BurdickUAI, 2020 |
 | Deep Inductive Matrix Completion for Biomedical Interaction PredictionHaohan Wang*, Yibing Wei*, Mengxin Cao*, Min Xu, Wei Wu, and Eric XingBIBM, 2019 |
![[poster]](https://raw.githubusercontent.com/MMPLab/TrackVerse/refs/heads/main/assets/trackverse_iccv_poster.png){kind=link}
Projects
 | 🐝 Honeybee Computational Visual System- A visual system to detect, track, and count honeybees in the real-world environments. [Demo]- Hierarchical crowdsourcing algorithm for dense objects annotation [Code] |
Awards
- Beijing Outstanding Graduates (with honors), 2019
- National Scholarship for Outstanding Students, 2016
Teaching
@ UW-Madison
CS/ECE 766 - Computer Vision (Spring 2024)
CS 769 - Advanced Natural Language Processing (Spring 2022)
CS 220 - Data Programming 1(Fall 2021)
@ Caltech
ACM 104 - Applied Linear Algebra (Fall 2020)
IDS 158 - Fundamentals of Statistical Learning (Spring 2020)
Ph1b - Electromagnetism (Applications) (Winter 2020)