Yiping Lu

Ph.D. student

Institute for Computational and Mathematical Engineering
School Of Engineering
Stanford University

Bachelor of Science(Honor Track)

Department of Scientific & Engineering Computing
School of mathematical sciences
Peking University

Email: yplu [at] stanford [dot] edu
Contact: Moving now... contact me by email!

Biography [CV]

I'm interested in all computational and statistical methods used in imaging and graphics. Now I am working on data scince, hoping to build the bridge between deep learning and PDE(variation), wavelets and other traditional data analysis methods. Although I'm not major in statistics or computer science, I interested in statical learning theroy applied in artificial intelligence. I am also working on learning on manifolds, mainly semi-supervised learning via diffusion or wavelets. At the same time, we want to bring insight to graph CNN designing.

I am also working on learning theory, uncertainty quantification, sparse coding, inverse problem and computer vision.


  • 2012-2015

    Shanghai High School

    Mathematics class

  • 2015-2019 (Expected)

    Peking University

    School of mathematical sciences, Department of Scientific & Engineering Computing

    Major:Information and Computing Science

Work Experience

  • Beijing International Center for Mathematical Research(BICMR), Peking University

    Research Intern(2016.12-present)

    Supported by the Elite Undergraduate Training Program of the School of Mathematical Sciences at Peking University and National innovation training project.

    Advisor:Prof. Bin Dong

  • Key Laboratory of Machine Perception (MOE), Peking Unviersity

    Research Intern(2017.12-present)

    Advisor:Prof. Liwei Wang

  • MIT CSAIL Geometry Data Processing Group, MIT

    Visiting Undergraduate Student(2018.6-2018.8)

    Advisor:Prof. Justin Solomon

  • Visual Computing Group, Microsoft Research Asia

    Research Intern(2018.11-2019.7)

    Advisor:David Wipf

  • Institute for Computational & Mathematical Engineering, Stanford

    PHD Student(2019.9-)

    For the moment, working with Prof. Leonidas Guibas, The Geometric Computation Group

Invited Talks

  • Dynamic View Of Deep Learning[ slide(2018.8version)]
    • Seminar for the elite phd students training program in applied and computational math. (Peking Univ. Math Department.)
    • Forum on Artificial Intelligence Frontiers.(Peking Univ. EECS Department.)
    • Machine Learning Theory Workshop (BEIJING INSTITUTE OF BIG DATA RESEARCH)
    • The Level Set Collective, UCLA, 2018/08

Honors & Awards

1st prize in Chinese Mathematical Olympiad 2013.12
2nd prize in Chinese Mathematical Olympiad 2014.12
DTZ/Cushman & Wakefield Scholarship 2015-206
Merit Student in PKU (top 5%) 2015-206
The elite undergraduate training program of Pure Math 2016-present
The elite undergraduate training program of Applied Math 2017-present


  • Providing problems and answers to "Elegant Solutions Winner" section in New Star Math.
  • Freshman instructor of Freshman Orientation 2016.9
  • Freshman instructor of Freshman Orientation 2017.9
  • Reviewer: ICCV 2019 ,SPARS 2019

© Yiping Lu | Last updated: 11/08/2018

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Theory without practice is empty, but equally, practice without theory is blind. ---- I. Kant

People who wish to analyze nature without using mathematics must settle for a reduced understanding. ---- Richard Feynman