About

I am a computer science engineer and applied mathematician specializing in High-Performance Computing (HPC), AI infrastructure, and mathematical optimization solver design. My work bridges the gap between complex mathematical theory and highly scalable, production-grade systems.

Work Experience Link to heading

HPC & AI Engineer @ Axians (a brand of VINCI Energies) Link to heading

Since 2024 | Toulouse, France

Architect and build enterprise-grade HPC and AI clusters from bare-metal hardware to user-facing middleware, maximizing CPU/GPU utilization for major industrial and academic clients.

• Full-Stack Cluster Architecture: Design, provision, and administer multi-tenant HPC and AI platforms, managing everything from bare-metal deployment (xCAT, Confluent, HPCM, BlueBanquise, Warewulf, Ansible) and distributed storage (GPFS, BeeGFS, Lustre) to high-speed interconnect topologies (InfiniBand, NVLink).
• Hybrid Workload Orchestration: Engineered and optimized unified orchestration workflows combining traditional batch scheduling (Slurm, Torque, LFS, PBS Pro) with modern containerized microservices (Kubernetes, OpenShift) to streamline heavy training and inference workloads.
• Self-Hosted Private AI Platform: Developed a secure, fully self-hosted platform enabling enterprise users to interact with private data using local LLMs, optimized for zero-leakage data privacy.
• Unified Data Science Portal: Built a web-based UI and resource-scheduling platform that abstracts complex cluster infrastructure, allowing data scientists to effortlessly submit jobs and deploy microservices across Slurm and Kubernetes.
• Local Inference Engineering: Designed and implemented highly optimized local LLM inference fabrics, maximizing hardware topology and low-latency interconnects to dramatically reduce latency and improve throughput for large-scale workloads.

Postdoctoral Fellow in Applied Mathematics @ PolyU Link to heading

2022 – 2024 | Hong Kong, China

Conducted advanced numerical analysis research and engineered high-performance, open-source mathematical optimization libraries widely integrated into global data science ecosystems.

• Global Ecosystem Integration: Engineered and successfully integrated the COBYQA solver directly into the core SciPy library, exposing advanced optimization algorithms to millions of developers and data scientists worldwide.
• Production-Grade Open-Source Architecture: Architected, maintained, and scaled COBYQA and PDFO, managing robust codebases, continuous integration pipelines, and cross-platform compatibility for complex derivative-free optimization solvers.
• Derivative-Free Algorithm Design: Designed and implemented cutting-edge numerical analysis algorithms specifically optimized for complex, high-dimensional engineering problems where mathematical derivatives are unavailable or computationally prohibitive to calculate.
• Peer-Reviewed Scientific Contributions: Authored and published original algorithmic research in premier international journals of applied mathematics and numerical optimization, defending technical methodologies to peer experts.

Education Link to heading

PhD in Applied Mathematics @ PolyU Link to heading

2019 – 2022 | Hong Kong, China

• Thesis: Model-Based Derivative-Free Optimization Methods and Software.
• Distinction: Recipient of the prestigious Hong Kong PhD Fellowship Scheme (HKPFS), awarded by the Research Grants Council to the top global doctoral applicants.
• Core Output: Conceived and engineered the core numerical frameworks for the COBYQA and PDFO open-source derivative-free optimization libraries.

MSc in Scientific Computing @ UT3 Link to heading

2018 – 2019 | Toulouse, France

• Specialization: High Performance in Software, Media, and Scientific Computing.

Diplôme d’Ingénieur in Computer Science & Applied Mathematics @ ENSEEIHT Link to heading

2016 – 2019 | Toulouse, France

• Specialization: HPC & Big Data (focus on parallel architectures, distributed computing, and large-scale data engineering).

CPGE in Mathematics & Physics @ Lycée Carnot Link to heading

2014 – 2016 | Dijon, France

• Intensive two-year undergraduate preparatory program in advanced mathematics, physics, and computer science for competitive entry into top-tier French Grandes Écoles.