Letao Wang

Researcher in Quantum Computing · Paris Region, France

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Hello! I’m a first-year PhD student in Quantum Machine Learning at the Laboratory of Signals and Systems (L2S), CentraleSupélec, Paris-Saclay University. My doctoral speciality is Mathematical Computer Science.

I completed my Master’s studies in Theoretical Computer Science and Quantum Physics at École Normale Supérieure Paris-Saclay (ENS Paris-Saclay), and my Bachelor’s degree in Computer Science at Université Paris Cité (formerly Université Paris-Descartes). I’m always happy to exchange ideas and collaborate, you can reach me by the email button below :)

My research interests include:

  • Quantum physics-informed neural networks (QPINNs)
  • Variational quantum algorithms for solving financial PDEs
  • Financial Mathematics (portfolio optimization)

News

Sep 14, 2026 QTML2026 My work Fourier Symmetrization for Geometric Quantum Machine Learning was accepted as a poster presentation at Quantum Techniques in Machine Learning (QTML) 2026.
Mar 12, 2026 Best Poster Award of the Quantum-Saclay Day for my work on Learning PDEs for portfolio optimization with quantum physics-informed neural networks

Publications

  1. arXiv
    Fourier Symmetrization for Geometric Quantum Machine Learning
    Letao Wang, Abdel Lisser, Sreejith Sreekumar, and 1 more author
    Oct 2026
    arXiv
  2. arXiv
    Learning PDEs for Portfolio Optimization with Quantum Physics-Informed Neural Networks
    Letao Wang, Abdel Lisser, Sreejith Sreekumar, and 1 more author
    Apr 2026
    arXiv
  3. Quantum Sci. Technol.
    Subspace preserving quantum convolutional neural network architectures
    Léo Monbroussou, Jonas Landman, Letao Wang, and 2 more authors
    Quantum Science and Technology, Mar 2025
    DOI HTML