I am a fourth-year Ph.D. student at University of Pennsylvania, advised by René Vidal. I work closely with Benjamin D. Haeffele and Yi Ma. Prior to my Ph.D., I spent two years as a research assistant at ShanghaiTech University, advised by Manolis C. Tsakiris and collaborating with Laurent Kneip. I received my undergraduate degree in computer science with honor from ShanghaiTech, working with Manolis and Yi.
My research interests lie in the theoretical foundations of machine learning and data science as well as emerging applications. As such, I develop both rigorous mathematics and practical implementations in my work. In particular, I study manifold learning and clustering, 3D vision and robotics.
I love to talk about ideas relevant to my work. If you are a student interested in doing research with me, please email me with your CV and transcript. For master’s students and undergraduates, the minimum time commitment is 15 hours per week for six months.
|One paper accepted to ICML 2022 and one to CVPR 2022!
|All papers have code available now.
|I shared some stories about my undergraduate career at the SIST website, ShanghaiTech.
- HARD: Hyperplane ARrangement DescentIn Conference on Parsimony and Learning (Proceedings Track), 2024
- Unsupervised Manifold Linearizing and ClusteringIn International Conference on Computer Vision, 2023
- Understanding Doubly Stochastic ClusteringIn International Conference on Machine Learning, 2022
- Efficient Maximal Coding Rate Reduction by Variational FormsIn IEEE Conference on Computer Vision and Pattern Recognition, 2022
- Robust Homography Estimation via Dual Principal Component PursuitIn IEEE Conference on Computer Vision and Pattern Recognition, 2020
- Noisy Dual Principal Component PursuitIn International Conference on Machine Learning, 2019
- Learning to parse wireframes in images of man-made environmentsIn IEEE Conference on Computer Vision and Pattern Recognition, 2018