cv

This is my CV.

General Information

Full Name Minh-Hai Nguyen
Website mh-nguyen712.github.io
Email nguyenhai7120qh@gmail.com
LinkedIn linkedin.com/in/mh-nguyen712
Phone +33 7 69 60 25 04
Languages English (professional), French (fluent), Vietnamese (native)

Summary

  • Third-year PhD candidate in the MAMBO team at Toulouse University (expected graduation in Dec. 2026), advised by Prof. Pierre Weiss and Prof. Edouard Pauwels.
  • Research focus on computational imaging with deep learning and generative models.
  • Active open-source contributor.

Education

  • 2023 - present
    PhD in Applied Mathematics
    Toulouse University, France
    • Inverse problems in imaging.
  • 2018 - 2023
    Master of Engineering in Applied Mathematics
    INSA Toulouse, France
    • Major in AI / Data Science.
  • 2015 - 2018
    Quoc Hoc Hue High School for Gifted Students
    Vietnam
    • Specialized in Mathematics.

Work Experience

  • Dec 2022 - Sept 2023
    Research Engineer
    Agenium Space
    • Corrected micro-vibrations in satellite imaging with pushbroom cameras.
    • Modeled the imaging process, implemented deep learning-based methods, and evaluated on real Sentinel-2B data.
  • Jun 2022 - Sept 2022
    Research Intern
    Toulouse Mathematics Institute
    • Product-convolution neural networks for image deblurring with space-varying blurs.
    • Collaboration with Pierre Weiss and Paul Escande.

Open-Source Projects

  • Ongoing
    Blind Deblurring in Fluorescence Microscopy
    • Deep learning methods to jointly estimate sharp image and unknown blur kernel from a single blurred fluorescence microscopy image.
    • Covers diffraction-limited blurs (Zernike polynomials), spatially varying blurs, and 2D/3D settings.
    • Efficient PyTorch implementation and ongoing validation on RIM, TIRF, and confocal settings.
    • Joint work with Pierre Weiss, Florian Sarron, Paul Escande, Thomas Mangeat, and Sylvain Cantaloube.
    • Presented at MIFOBIO-25.
  • 2023 - present
    DeepInverse - Core contributor and maintainer
    • Open-source PyTorch library in the PyTorch Ecosystem for imaging inverse problems.
    • Contributed to API design, benchmarks, CI/CD, packaging, documentation, and community support.

Skills

  • Programming
    • Python, PyTorch (advanced), GPU programming.
    • Triton/CUDA kernels (intermediate), JAX, C++ (intermediate).
    • Large-scale training (DDP/FSDP) on GPU clusters (Jean-Zay).
    • Profiling and optimization (Nsight, torch-profiler).
  • Development
    • Linux, Git/GitHub, packaging (PyPI), conda/uv/docker environments.
    • SOTA implementation and evaluation, model training and fine-tuning.
  • Research
    • Image restoration, computational imaging, deep learning.
    • Deblurring/denoising, generative models, CNNs, Transformers, diffusion/flow models.

Talks and Presentations

  • Apr 2026

    Paris, France

    PyTorch Conference Europe 2026 (Speaker)
    • Title: DeepInverse and Computational Imaging.
  • Oct 2025

    Marseille, France

    Blind inverse problems in imaging from foundations to applications
    • Title: How diffusion prior landscapes shape the posterior in blind deconvolution.
  • Aug 2025

    Strasbourg, France

    GRETSI 2025 (Oral)
    • Title: How diffusion prior landscapes shape the posterior in blind deconvolution.
  • Mar 2025

    Nice, France

    IABM (Poster)
    • Title: Deep learning-based blind deblurring in microscopy.
  • Oct 2023

    Marseille, France

    30 Years of Mathematics for Optical Imaging (Oral)
    • Title: DeepVibes: Correcting Microvibrations in Satellite Imaging With Pushbroom Cameras.

Teaching

  • 2023 - present
    Teaching Assistant (Vacataire)
    INSA Toulouse
    • Signal Processing.
    • Stochastic Optimization (32 hours per year).

Distinctions

  • Nov 2024
    • French National Prize for Open Science Library for DeepInverse.
  • 2023 - 2026
    • Doctoral Research Fellowship, French Ministry of Higher Education and Research.
  • 2023
    • IA Pau Winner.

Other Interests

  • Hobbies: Football, Running, Swimming.