I am currently a Ph.D. candidate in CSE department of Hong Kong University of Science and Technology (HKUST), supervised by Prof. Dit-Yan Yeung. Previously, I was an undergraduate student majoring in Computer Science in Fudan University honored as the Outstanding Undergraduate of Shanghai (上海市优秀毕业生), supervised by Prof. Yanwei Fu. My research interests include Machine Learning and Artificial Intelligence, aiming at building generalizable AI systems from a data-centric perspective. Currently, I'm trying to answer, 1) Does more data always result in better performance? 2) How to generate corner cases with generative models? 3) How to fix corner cases with minimum human intervention?
👋 I'm on job market of both academics and industry for Fall 2025. Feel free to send me emails if we are a good fit!
Some recent works include:
Full publication list on Google Scholar. (* denotes equal contribution)
Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation
European Conference on Computer Vision (ECCV), 2024.
Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis
International Conference on Learning Representations (ICLR), 2024.
Task-customized Masked Autoencoder via Mixture of Cluster-conditional Experts
International Conference on Learning Representations (ICLR), 2023 (spotlight Top25%).
Task-Customized Self-Supervised Pre-training with Scalable Dynamic Routing.
AAAI Conference on Artificial Intelligence (AAAI), 2022.
Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.
CODA: A Real-World Corner Case Dataset for Object Detection in Autonomous Driving
European Conference on Computer Vision (ECCV), 2022.
Workshop of Automonous Driving, Vision and Learning Seminar (VALSE), 2023 (spotlight).
Implicit Concept Removal of Diffusion Models
European Conference on Computer Vision (ECCV), 2024.
TrackDiffusion: Tracklet-Conditioned Video Generation via Diffusion Models
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.
MagicDrive: Street View Generation with Diverse 3D Geometry Control
International Conference on Learning Representations (ICLR), 2024.
GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation
International Conference on Learning Representations (ICLR), 2024.
Mixed Autoencoder for Self-supervised Visual Representation Learning
IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2023.
Workshop of Self-supervised Learning, Vision and Learning Seminar (VALSE), 2023 (spotlight).
MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving
IEEE/CVF International Conference on Computer Vision (ICCV), 2021.
SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving.
Datasets and Benchmarks Track, Neural Information Processing Systems (NeurIPS), 2021.
HKUST Research Travel Grant
HKUST Postgraduate Scholarship
Outstanding Graduate of Shanghai [post]
Scholarship for Outstanding Graduates of Fudan University
Joel & Ruth Spira Scholarship
Oversea Visiting Student Stipend of Fudan University
National Scholarship
Scholarship for Outstanding Undergraduates of Fudan University
I love basketball and I'm also a big fan of Stepfen Curry, MVP point guard of Golden State Warriors, NBA. I'm a team member of my class's basketball team and often play Score / Power forward (SF/PF). In my spare time, I also play the role of a basketball game referee. Hope one day I can have a chance to see a home game of Warriors in Chase Center San Francisco!