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I am an assistant professor in the Department of Computer Science in the University of Texas at Dallas. I was a postdoc at UC Berkeley/ICSI working with Prof. Stella Yu. Previously, I completed my PhD at the University of California San Diego advised by Prof. Tajana Rosing. During my PhD, I had the pleasure to spent time at Qualcomm AI research and IBM Thomas J. Watson Research Center. Email: yunhui.guo (at) utdallas.edu I am looking for self-motivated PhD students and Research Interns. If you have experience in computer vision or machine learning and are interested in solving challenging research problems in these areas, please send me your CV and transcripts. |
Recent News
(09/2025) One paper on multimodal robustness has been accepted to NeurIPS 2025 (D&B track)!
(08/2025) I will be serving as an Area Chair for CVPR 2026.
(06/2025) One paper accepted by ICCV 2025 and one paper accepted by IROS 2025. Congratulations to all co-authors!
(05/2025) Our 1st Workshop on Multimodal Continual Learning will be held at ICCV ’25 in Honolulu, Hawai‘i. Please consider submitting your work!
(04/2025) Our 2nd Workshop on Test-Time Adaptation: Putting Updates to the Test! (PUT) will be held on July 18–19, 2025, at ICML '25 in Vancouver. Please consider submitting your work!
(02/2025) Our paper on continual out-of-distribution detection accepted at CVPR 2025.
(12/2024) Our project has been selected by the Nvidia Academic Grant Program.
(12/2024) One paper on test-time adaptation has been accepted for an Oral Presentation at AAAI 2025. Congratulations to Sarthak!
(09/2024) Two papers were accepted by NeurIPS 2024. Congratulations to my students!
(09/2024) I will be serving as an Area Chair for CVPR 2025.
(07/2024) One paper about deep neural network watermarking was accepted by ECCV 2024. Congratulations to my students!
(05/2024) One paper is early accepted (top 11%) by MICCAI 2024.
(02/2024) Unsupervised Hyperbolic Feature Learning and Segment Every Out-of-Distribution Object are accepted by CVPR 2024.
(01/2024) I will be serving as an Area Chair for ECCV 2024.
Research
My research is at the intersection of machine learning and computer vision. The goal of my lab is to investigate, design, and develop intelligent vision systems capable of reliable deployment in real-world scenarios. Currently, my research focuses on constructing intelligent agents that can continuously learn, dynamically adapt to evolving environments without forgetting previously acquired knowledge, and repurpose existing knowledge to adapt to novel scenarios. Our work paves the way for building intelligent and reliable systems in IoT, mobile computing, and autonomous driving, with the long-term goal of making AI more accessible and robust.
Group
Ph.D. Students
- Ouyang Xu (Fall 2022. B.S. from Southeast University, M.S. from University of Wisconsin–Madison.)
- Wenjie Zhao (Fall 2023. B.S. from Sichuan University, M.S. from Xi'an Jiaotong University.)
- Sarthak Kumar Maharana (Fall 2023. B.S. from International Institute of Information Technology Bhubaneswar, M.S. from the University of Southern California.)
- Ruiyu Mao (B.S from Case Western Reserve University, M.S. from the University of Texas at Dallas.)
Master Students
- Subhrangsu Bose (UT Dallas)
Undergraduate Students
- Nhi Le (UT Dallas)
- Zhixuan Wu (UMich)
Intern
- Haoran Guo (UC Berkeley)
- Yuxuan Li (Harbin Institute of Technology)
Selected Publications
Oral presentation
Oral presentation
Spotlight, top 4% submissions
Teaching
- Instructor: UT Dallas CS 4365 Artificial Intellgence (Fall 2022, Spring 2023, Fall 2023, Fall 2024), Computer Vision (Spring 2025)
© Yunhui Guo 2017