Willem Diepeveen
Portrait
Logo Hedrick Assistant Adjunct Professor, Department of Mathematics, UCLA

I am a Hedrick Assistant Adjunct Professor in the Department of Mathematics at UCLA, hosted by Deanna Needell and Andrea Bertozzi, where I also work closely with Oscar Leong. Previously, I completed my PhD at University of Cambridge, supervised by Carola-Bibiane Schonlieb, and hold a double MSc from TU Delft and TU Berlin, and a double BSc from TU Delft.

My research bridges Riemannian geometry, machine learning, and signal processing, which I use to develop interpretable and theory-grounded machine learning approaches for inverse problems, manifold learning, and data-driven modeling in the sciences.

Beyond research, I enjoy teaching mathematics at UCLA, mentoring graduate and undergraduate students, and engaging in interdisciplinary collaborations. I am also an avid sailor, hiker, skier and snowboarder, and a classics and poetry enthusiast.

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Education
  • University of Cambridge
    University of Cambridge
    PhD Mathematics
    Thesis: Riemannian Geometry for Inverse Problems in Cryogenic Electron Microscopy
    Advisor: Carola-Bibiane Schonlieb
    Oct 2020 – Jun 2024
  • TU Delft & TU Berlin (double degree)
    TU Delft & TU Berlin (double degree)
    MSc Applied Mathematics & MSc Scientific Computing
    Sep 2018 – Sep 2020
  • TU Delft (double degree)
    TU Delft (double degree)
    BSc Applied Mathematics & BSc Applied Physics
    Sep 2014 – Aug 2017
Experience
  • University of California, Los Angeles
    University of California, Los Angeles
    Hedrick Assistant Adjunct Professor, Department of Mathematics
    Host: Deanna Needell and Andrea Bertozzi
    Jul 2024 - Present
  • Harvard University
    Harvard University
    Visiting Postdoctoral Fellow, John A. Paulson School of Engineering and Applied Sciences
    Host: Melanie Weber
    Jun 2025 - Sep 2025
  • Institute for Pure and Applied Mathematics
    Institute for Pure and Applied Mathematics
    Fellow, Long Program on "Computational Microscopy"
    Oct 2022 - Dec 2022
News
2025
Our paper with Jon and Andrea on interpretable latent dynamics modeling has been accepted to Applied Mathematics Letters.
Jul 23
For the summer, I joined Harvard University as a Visiting Postdoctoral Fellow in the Geometric Machine Learning Group.
Jul 01
New preprint out with Deanna on iso-Riemannian geometry for Riemannian manifold learning.
May 13
Our paper with Georgios, Zak and Carola on scaling up learned pullback geometry has been accepted to ICML 2025.
May 01
2024
I joined the Department of Mathematics at UCLA as Hedrick Assistant Adjunct Professor.
Jul 02
Selected Publications (view all )
Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows

Willem Diepeveen*, Georgios Batzolis*, Zakhar Shumaylov, Carola-Bibiane Schonlieb (* equal contribution)

ICML 2025

[Paper] [Code]

Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows

Willem Diepeveen*, Georgios Batzolis*, Zakhar Shumaylov, Carola-Bibiane Schonlieb (* equal contribution)

ICML 2025

[Paper] [Code]

Riemannian Geometry for Efficient Analysis of Protein Dynamics Data

Willem Diepeveen, Carlos Esteve-Yague, Jan Lellmann, Ozan Oktem, Carola-Bibiane Schonlieb

Proceedings of the National Academy of Sciences 2024

[Paper] [Code]

Riemannian Geometry for Efficient Analysis of Protein Dynamics Data

Willem Diepeveen, Carlos Esteve-Yague, Jan Lellmann, Ozan Oktem, Carola-Bibiane Schonlieb

Proceedings of the National Academy of Sciences 2024

[Paper] [Code]

Curvature Corrected Tangent Space-based Approximation of Manifold-valued Data

Willem Diepeveen, Joyce Chew, Deanna Needell

Preprint (accepted to Information and Inference) 2023

[Paper] [Code]

Curvature Corrected Tangent Space-based Approximation of Manifold-valued Data

Willem Diepeveen, Joyce Chew, Deanna Needell

Preprint (accepted to Information and Inference) 2023

[Paper] [Code]

All publications