CV

General Information

Summary

  • Final-year PhD candidate in AI & Computer Vision at École Polytechnique. My research focuses on transfer learning for 3D data, with a proven track record of developing effective pre-training and fine-tuning strategies for shape analysis (classification, segmentation, retrieval) and cross-modal (image and text) applications.

Technical Skills

Languages Python, SQL, MATLAB, R
Frameworks PyTorch, TensorFlow, Scikit-learn
Areas of Expertise Machine Learning, Deep Learning, 2D & 3D Computer Vision, Natural Language Processing, LLM, Generative Modeling, Computer Graphics, Optimisation

Education

  • Jan 2023 – 2026
    PhD Student
    École Polytechnique, France
    • Supervised by Prof. Maks Ovsjanikov.
  • 2022
    M2 Master: MVA (Mathematics, Vision, Learning)
    École Normale Supérieure Paris-Saclay, France
    • GPA: 4.0
  • 2022
    Master of Engineering (Major in Mathematics, Specialization in Data Science)
    CentraleSupélec, France
    • GPA: 4.0
  • 2019
    Bachelor of Engineering
    CentraleSupélec, France

First Author Publications

  • 2026
    PatchAlign3D: Local Feature Alignment for Dense 3D Shape Understanding
    ArXiv Preprint
    • Souhail Hadgi, Bingchen Gong, Ramana Sundararaman, and 4 more authors.
    Project
    arXiv
    PDF
  • 2025
    Escaping Plato’s Cave: Towards the Alignment of 3D and Text Latent Spaces
    CVPR 2025
    • Souhail Hadgi, Luca Moschella, Andrea Santilli, Diego Gomez, Qixing Huang, Emanuele Rodolà, Simone Melzi, Maks Ovsjanikov.
    arXiv
    PDF
  • 2024
    To Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of Point Cloud Transfer Learning
    ECCV 2024
    • Souhail Hadgi, Lei Li, Maks Ovsjanikov.
    arXiv
    PDF

Experience

  • May 2022 – Oct 2022
    Research Intern
    École Polytechnique
    • Analysis of several unsupervised pre-training approaches for 3D representation learning.
    • Adapted scene point-level contrastive learning approaches for 3D shape analysis.
  • Aug 2020 – Jul 2021
    Data Scientist Intern
    DataScientest
    • Designed Computer Vision modules for a Deep Learning curriculum.
    • Supervised Deep Learning applied projects.
    • Conceived the scientific content of data challenges.
    • Taught Deep Learning courses for cohorts of learners.

Teaching

  • Analysis and Deep Learning on Geometric Data — CSC 53431 EP — École Polytechnique (2024/2025)
  • Machine Learning — CSE204 — École Polytechnique (2023/2024)
  • Advanced Programming — CSE102 — École Polytechnique (2023/2024)

Projects

  • Reconcile video predictions from multiple angles
    Sicara
    • Created a TensorFlow pipeline that generates videos of highways corresponding to a different view angle from the initial viewpoint.
    • Optimized an auto-encoder architecture for image generation.
  • Segmentation models for audio data
    Illuin Technology
    • Created an end-to-end PyTorch deep learning pipeline for speaker diarisation.
    • Trained and evaluated the diarisation pipeline on the TCOF dataset.