Ph.D. in Electronic Engineering
The Chinese University of Hong Kong (CUHK), 2021–2026
Advisor: Prof. Yixuan Yuan
About
I am a final-year Ph.D. student in the Department of Electronic Engineering at the Chinese University of Hong Kong (CUHK), supervised by Prof. Yixuan Yuan. Prior to that, I received my B.Eng. in Electronic Information Engineering from Huazhong University of Science and Technology (HUST) in 2021. During my Ph.D., I have been fortunate to work with Dr. Zhenwei Wang and Dr. Tengfei Wang at the Tencent HY 3D Generation Team. I have also been fortunate to collaborate with industry, particularly with Tencent HY and ByteDance Seed.
My research focuses on video and 3D world models, 3D reconstruction, and generative AI, with an emphasis on building generalizable systems for immersive and interactive world understanding and generation.
I'm always open to related discussions and collaborations. If you are interested in my work, please feel free to contact me.
Education
B.Eng. in Electronic Information Engineering
Huazhong University of Science and Technology (HUST), 2017–2021
Experience
- Research Intern, Tencent HY, Video World Model Team
- Research Intern, Tencent HY, 3D Generation Team
Open-Source Projects
HY-World 1.1
A 3D world reconstruction framework capable of producing immersive, explorable, and interactive scenes from arbitrary-view inputs.
Selected Publications [full list]
(*equal contribution)
WorldMirror: Universal 3D World Reconstruction with Any-Prior Prompting
A universal 3D reconstruction framework capable of processing diverse input modalities and generating various output representations.
MonoSplat: Generalizable 3D Gaussian Splatting from Monocular Depth Foundation Models
A generalizable 3D Gaussian Splatting approach from monocular depth foundation models.
InstantSplamp: Fast and Generalizable Stenography Framework for Generative Gaussian Splatting
A framework for embedding imperceptible, recoverable information in 3D generative model renders.
Foundation Model-guided Gaussian Splatting for 4D Reconstruction of Deformable Tissues
The first work to apply 3D Gaussian Splatting for dynamic (4D) endoscopic reconstruction, guided by foundation models.
U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation
Introducing Kolmogorov-Arnold Networks (KANs) as a strong backbone for medical image segmentation and generation.
GaussianReg: Rapid 2D/3D Registration for Emergency Surgery via Explicit 3D Modeling with Gaussian Primitives
Rapid 2D/3D registration for emergency surgery using sparse Gaussian primitives and a ray-based registration scheme.
Selected Honors
- Golden Reviewer Award, ICML 2026
- Postgraduate Studentship, CUHK, 2021–2026
- First Class Scholarship, 2019–2020
- Scholarship of Academic Excellence, 2017–2020
- Outstanding Graduates of Huazhong University of Science and Technology, 2021
Academic Services
- Conference Reviewer: CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, ICRA, IROS
- Journal Reviewer: IJCV, TPAMI, TVCG, TNNLS, TCSVT, TMM, TMI, MIA
Miscellaneous
Curiosity and enthusiasm shape both my research and my life. I'm also passionate about basketball🏀, hiking⛰️, swimming🏊♂️, table tennis🏓, and badminton🏸.