CV
Basics
| Name | Pierre Joly |
| pierre.joly2001@gmail.com | |
| Summary | Machine Learning Research Engineer with an applied mathematics background, working on the theoretical and experimental foundations of modern deep learning. |
Work
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2025.04 - 2025.09 Research Intern - Representation Control in Text-to-Image Models
CISPA Helmholtz Center for Information Security
Research internship at the SprintML Lab in CISPA, supervised by Dr. Boenisch and Dr. Dziedzic.
- Work submitted to ICLR 2026.
- Investigating and prototyping novel methods tocontroland remove targeted semantic concepts in Text-to-Image Models.
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2023.05 - 2023.10 Research Intern – Robustness & Uncertainty in Object Detection
CEA (French Alternative Energies and Atomic Energy Commission)
Research internship at the AIC Chair in CEA List, supervised by Dr. Tamaazousti.
- Co-authored two patents: EP4575900 and EP4592898.
- Researched and developed two novel methods for certifiable robustness and uncertainty quantification in object detection tasks, utilizing YOLOv3 and YOLOv8 algorithms.
Volunteer
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2022.04 - 2023.04 IT Manager
Challenge Centrale Lyon
Part of a team of 19 students organizing a student sports competition for over 3,000 participants.
- Designed and developed the entire event website independently.
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2022.01 - 2023.01 Treasurer of the External Relations Section
AEECL - Association des Élèves de l'Ecole Centrale de Lyon
Managed the budget and financial operations of the External Relations Section for a one-year term.
- Managed a budget of €50k.
- Collaborated with other board members to ensure the successful organization and execution of events and initiatives.
Education
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2021.09 - 2025.09 Lyon, France
Master of Science (Grande École Program)
École Centrale de Lyon
General Engineering, Mathematics Specialization
- Sparsity & High-Dimensional Data
- Convex Optimization
- Bayesian Statistics
- Functional Analysis (PDEs)
- Stochastic Differential Equations
- Machine Learning
- Quantum Information
- Multiphysics Simulation
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2019.09 - 2021.07 Toulouse, France
Preparatory Program
Lycée Déodat de Séverac
Mathematics and Physics (Classes Préparatoires PCSI–PSI*)
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2016.09 - 2019.07 France
Certificates
| Fundamentals of Reinforcement Learning | ||
| University of Alberta | 2023-12-01 |
| Deep Learning Specialization | ||
| DeepLearning.AI | 2023-11-01 |
| TOEFL ITP (607/677) | ||
| ETS EMEA | 2023-04-01 |
| PSC1 - First Aid and Civic Rescue Training | ||
| Ministère de la Santé | 2022-11-01 |
| Brevet de base de pilote d'avion | ||
| FFA – Fédération Française Aéronautique | 2018-07-01 |
| Brevet d'Initiation Aéronautique | ||
| Education nationale | 2017-01-01 |
Skills
| Machine Learning | |
| Deep Learning | |
| Reinforcement Learning | |
| Bayesian Inference | |
| Gaussian Processes | |
| Variational Inference |
| Mathematics | |
| Optimization | |
| Statistics | |
| Functional Analysis | |
| Stochastic Processes | |
| PDEs | |
| Linear Algebra |
| Programming | |
| Python | |
| C++ | |
| Swift | |
| Bash | |
| SQL | |
| PyTorch | |
| JAX |
| HPC & Simulation | |
| Metal GPU Programming | |
| Slurm HPC Scheduler | |
| Numerical Simulation |
Languages
| French | |
| Native |
| English | |
| Fluent (TOEFL ITP 607/677) |
| Spanish | |
| Beginner |
| Chinese | |
| Beginner |
Interests
| AI for Science | |
| Generative Models | |
| Bayesian Inference | |
| Physics Simulations | |
| Scientific Machine Learning |
Projects
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Deep Kernel Learning Variational Inference
Co-authored a mathematical report on scalable Bayesian inference with Gaussian processes, combining theoretical insights and code illustrations, focusing on variational inference and dimensionality reduction via Deep Kernel Learning.
- Implemented exact and variational GP inference
- Integrated neural networks for kernel learning
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SPH Fluid Simulation in Metal
Developed a Smooth Particle Hydrodynamics (SPH) fluid simulation using Apple's Metal GPU framework to demonstrate fundamentals of SPH numerical simulation.
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Challenge Centrale Lyon Website Development
Developed the event website for a student sports competition with over 3,000 participants.