About me

I am a final-year PhD candidate in the Department of Computer Sciences at 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.

I am actively looking for Research Scientist / Applied Scientist / Research Engineer positions starting in 2026.

News

[June 2025] Our paper on TrackVerse, an object-centric video dataset for SSL, accepted at ICCV 2025.
[May 2025] Joined Adobe Firefly as an ML Research Intern!
[Feb 2025] Our paper on Accelerating the pretraining of vision transformers accepted at NeurIPS 2024.
[July 2024] Our paper on Latent MIM accepted by ECCV 2024.

Publications

	TrackVerse: A Large-Scale Object-Centric Video Dataset for Image-Level Representation Learning Yibing Wei, Samuel Church, Victor Suciu, Jinhong Lin, Cheng-En Wu, Pedro Morgado ICCV, 2025 [paper] [supp] [code] [dataset] [poster]
	Towards Latent Masked Image Modeling for Self-Supervised Visual Representation Learning Yibing Wei, Abhinav Gupta, Pedro Morgado ECCV, 2024 [paper] [code] [project page]
	Accelerating Augmentation Invariance Pretraining Jinhong Lin,Cheng-En Wu, Yibing Wei, Pedro Morgado NeurIPS, 2024 [paper]
	Multispectral Masked Autoencoder for Remote Sensing Representation Learning Yibing Wei, Zhicheng Yang, Hang Zhou, Mei Han,Jui-Hsin Lai. NeurIPS, WiML Workshop, 2023 [doc]
	Dueling Posterior Sampling for Preference-Based Reinforcement Learning Ellen Novoseller, Yibing Wei, Yanan Sui, Yisong Yue, and Joel W Burdick UAI, 2020 [paper] [code]
	Deep Inductive Matrix Completion for Biomedical Interaction Prediction Haohan Wang*, Yibing Wei*, Mengxin Cao*, Min Xu, Wei Wu, and Eric Xing BIBM, 2019 [paper]

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)