Cheng-Yao (Sean) Hong
Ph.D. Student
Computer Science, Stony Brook University
I am a first-year Ph.D. student in Computer Science at Stony Brook University, advised by Prof. Chenyu You. My research broadly lies in computer vision, multimodal learning, and generative models.
Before joining Stony Brook University, I worked as a Research Assistant at the Institute of Information Science (IIS), Academia Sinica, advised by Prof. Tyng-Luh Liu. I have also worked with Prof. Hwann-Tzong Chen and Prof. Ming-Sui Lee.
I received my M.S. degree from the Graduate Institute of Electronics Engineering (GIEE), National Taiwan University (NTU), where I was a member of the Integrated Circuits & Systems (ICS) Group. I received my B.S. degree from the Department of Electronics Engineering at National Chiao Tung University (NCTU). (Fun fact: My undergraduate university and department were both reorganized after I graduated. 😅)
Research Interests
My research focuses on building efficient multimodal and generative models that can understand, reason about, and interact with the physical world.
- Efficient Multimodal and Generative Models: Improving visual and multimodal models through efficient representation learning, token reduction, and test-time mechanisms.
- World Models and Embodied AI: Learning representations that support reasoning, planning, and interaction in dynamic environments.
- Dynamic and 3D Visual Understanding: Studying event-based vision, 3D perception, and robust scene understanding under fast-changing conditions.

News
| Jul 01, 2026 | One paper was accepted to ECCV 2026! |
|---|---|
| Sep 18, 2025 | One paper was accepted to NeurIPS 2025! |
| Dec 09, 2024 | One paper was accepted to AAAI 2025! |
| Feb 27, 2024 | One paper was accepted to CVPR 2024! |
| Dec 04, 2023 | Website launching now! |
Selected Publications (Full list)
(
The preview images are zoomable.)
Academic Services
I have served as a reviewer for CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, AAAI, and ICASSP, as well as for journals including TPAMI, TCYB, TNNLS, TNN, and Pattern Recognition.