全时教师
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黄儒麒

助理教授
学科领域:
邮箱: ruqihuang@sz.tsinghua.edu.cn
电话:
办公地址:
个人网站: rqhuang88.github.io
谷歌学术网站:
  • 个人简历BIOGRAPHY
  • 教育背景EDUCATION BACKGROUND

    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 stabilityproperties 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.

    2007–2011Tsinghua University, Beijing, China.

  • 学术背景ACADEMIC BACKGROUND
  • 工作经历PROFESSIONAL EXPERIENCE

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

    Assistant Professor

    2017–2019 Stream group, LIX, Ecole Polytenique.

    Post-doc Researcher

  • 学术任职ACADEMIC APPOINTMENTS
  • 额外职务ADDITIONAL POSITIONS
  • 学术职务ACADEMIC APPOINTMENTS
  • 访问经历VISITING EXPERIENCE
  • 业界经历INDUSTRIAL EXPERIENCES
  • 学术兼职PROFESSIONAL AFFILIATIONS AND ACTIVITIES
  • 兼职情况AFFILIATIONS AND ACTIVITIES
  • 社会兼职SOCIAL APPOINTMENTS
  • 会议组织CONFERENCE ORGANIZATION
  • 实习INTERNSHIP
  • 研究RESEARCH
  • 研究及教学领域RESEARCH AND TEACHING AREAS
  • 研究领域及专长RESEARCH INTEREST AND EXPERTISE

    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.

  • 研究课题RESEARCH TOPIC
  • 研究项目RESEARCH PROJECTS
  • 研究成果RESEARCH RESULTS
  • 科研经历RESEARCH EXPERIENCE
  • 研究经费RESEARCH GRANTS
  • 荣誉和奖项HONORS & AWARDS
  • 专业服务PROFESSIONAL SERVICE
  • 学术服务ACADEMIC APPOINTMENTS
  • 高校服务UNIVERSITY SERVICE
  • 语言LANGUAGE
  • 教学TEACHING
  • 课程COURSES
  • 硕士生&博士生指导MASTER'S & PHD ADVISING
  • 学术成果ACADEMIC ACHIEVEMENTS
  • 成就(包括出版物、专利、特邀报告、演讲等)ACHIEVEMENTS (INCL. PUBLICATIONS,PATENTS, INVITED TALKS, LECTURES, ETC.)
  • 出版物与专利PUBLICATIONS & PATENTS

    [* 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.

  • 报告与演讲TALKS & LECTURES
  • 活动ACTIVITIES
  • 毕业生ALUMNI
  • 学生和博士后STUDENTS AND POSTDOCS
  • 招生及博士后招聘OPENING