Ruqi Huang

2013-2016 University of Paris-Saclay, Paris, France.

Ph.D., Computer Science, December 2016.

Thesis: Two contributions to geometric data analysis: filamentary structures approximations, and stability properties of functional approaches for shape comparison.

Advisor: Frédéric Chazal

2011–2013 Tsinghua University, Beijing, China.

M.S., Computational Mathematics, December 2013.
Advisor: Fengshan Bai
B.S., Mathematics and Applied Mathematics, July 2011.

Thesis: Non-negative matrix factorization in network data dimension reduction.

2007–2011 Tsinghua University, Beijing, China.

2020–Present Tsinghua-Berkeley Shenzhen Institute, Tsinghua University.

Assistant Professor

2017–2019 Stream group, LIX, Ecole Polytenique.

Post-doc Researcher

My research interest lies in the area of Geometry Processing and 3D Computer Vision. In general, I am interested in problems from shape analysis, such as finding correspon- dences, understanding collections of 3D objects, and manipulating/synthesizing new 3D objects. I am also interested in practical applications related to computer vision, such as medical imaging data analysis.

[* indicates being corresponding author]

1. “Gromov-Hausdorff Approximation of Filamentary Structures Using Reeb-Type Graphs.”, F. Chazal, R. Huang, J. Sun. Discrete Computational Geometry, 2015.

2. “On the Stability of Functional Maps and Shape Difference Operators., R. Huang, F. Chazal, M. Ovsjanikov. Computer Graphics Forum, 2017.

3. “Adjoint Map Representation for Shape Analysis and Matching., R. Huang, M. Ovsjanikov. Symposium on Geometry Processing, 2017.

4. “Limit Shape – A Tool for Understanding Shape Differences and Variablity in 3D Model Collections, R. Huang, P. Achlioptas, L. Guibas, M. Ovsjanikov. Symposium on Geometry Processing, 2019.

5. “OperatorNet: Recovering 3D Shapes From Difference Operators, R. Huang, M. Rakotosaona, P. Achlioptas, L. Guibas, M. Ovsjanikov. International Conference on Computer Vision, 2019.

6. “Consistent ZoomOut: Efficient Spectral Map Synchronization, R. Huang, J. Ren, P. Wonka, M. Ovsjanikov. Symposium on Geometry Processing, 2020.

7. “EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation, Y. Zhao, M. Ji, R. Huang*, B. Wang, S. Wang, CAAI International Conference on Artificial Intelligence, 2021.

8. “Cross-Camera Deep Colorization”, Y. Zhao, H. Zheng, M. Ji, R. Huang*, CAAI International Conference on Artificial Intelligence, 2022.(Oral presentation)

9. “ParseMVS: Learning Primitive-aware Surface Representations for Sparse Multi-view Stereopsis”, H. Ying, J. Zhang, Y. Chen, Z. Cao, J. Xiao, R. Huang*, L. Fang*, ACM Int. Conf. on Multimedia 2022.

10. “ElasticMVS: Learning Elastic Part Representation for Self-supervised Multi-view Stereopsis”, J. Zhang, R. Tang, Z. Cao, J. Xiao, R. Huang*, L. Fang*, NeurIPS, 2022. (Spotlight)

11. “Optical Neural Ordinary Differential Equations”, Y. Zhao, H. Chen, M. Lin, H. Zhang, T. Yan, R. Huang, X. Lin, Q. Dai, Optics Letters, 48(3), 628-631, 2023.

12. “Neural Intrinsic Embedding for Non-rigid Point Cloud Matching”, P. Jiang, M. Sun, R. Huang*, IEEE CVPR, 2023.