Education

• 
  Sep 2026 – Dec 2027 (expected) · New York, NY

  Columbia University — Fu Foundation School of Engineering and Applied Science

  • M.S. in Artificial Intelligence, concentration in Robotics and Perception
  • STEM-designated; F-1, CPT-eligible for Summer 2027
  • Fall 2026
    • COMS W4731 — Computer Vision I: First Principles (Shree Nayar)
    • COMS W4733 — Computational Aspects of Robotics (Yunzhu Li)
    • IEOR E4742 — Deep Learning for Operations Research & Financial Engineering (Ali Hirsa)
    • IEOR E4010 — AI for Operations Research & Financial Engineering (RL, LLMs, multi-agent systems)
  • Spring 2027 (planned)
    • COMS W4732 — Computer Vision II: Learning
    • ELEN E6908 — Embedded AI
    • MECE E6616 — Robot Learning
    • MECE E6615 — Advanced Robotic Manipulation
    • COMS W4710 — Ethical and Responsible AI
• 
  2024 – 2026 · 129 ECTS · France

  Télécom SudParis — Institut Mines-Télécom / Institut Polytechnique de Paris

  • Diplôme d'Ingénieur (French engineering degree, master's level)
  • Advanced track: Statistical Modeling & Applications
  • Key courses
    • MAT 4251 / 4252 — Statistical Learning I & II
    • MAT 4102 — Machine Learning, Automatic Classification and Data Mining
    • MAT 4515 — Continuous Optimization for Learning and Machine Learning
    • MAT 4514 — Stochastic Processes (Kalman and particle filtering, HMMs)
    • MAT 4201 — Bayesian Inference in Markovian Models
    • SIC 3601 / 4103 — Signal Theory; Compression, Coding and Modulation
    • CSC 4103 — System Programming in C
    • PRO 4501 — Cassiopée industrial R&D project, 180 h (18/20)
• 
  2022 – 2024 · Nice

  Lycée Masséna — Classes préparatoires MPSI / MP

  • Two-year intensive mathematics and physics program
  • 12 h of mathematics a week, weekly written and oral exams
  • Admission to engineering school by national competitive examination
• 
  2022 · Nice

  Baccalauréat général — Lycée des Eucalyptus

  • 18.82/20, highest honors with the jury's commendation
  • Mathematics, Physics–Chemistry, Engineering Sciences

Skills

• Programming: Python, Java, C, SQL, Bash, JavaScript
• Machine learning: PyTorch, TensorFlow/Keras, scikit-learn, AutoGluon (CatBoost, XGBoost, LightGBM); fine-tuning, model validation, evaluation design
• Computer vision & perception: OpenCV, DETR / RF-DETR, ByteTrack, camera calibration (DLT), multiple-view geometry, triangulation, spectrogram-based audio classification
• Robotics & embedded: NVIDIA Jetson, TensorRT, ROS, MAVLink, DJI SDK, Arduino; A* / RRT planning, Kalman and particle filtering
• Decision & formal methods: Uppaal Stratego, Markov decision processes, convex optimization, MBSE (UAF / SysML, CATIA Magic)
• Tooling: pandas, NumPy, MariaDB / PostgreSQL, Docker, Git & GitHub Actions, Linux, LaTeX

Spoken languages

• French — native
• English — C1
• Spanish — B2