Xavier Gillard is an AI/ML engineer and technical leader with a PhD in computer science and over a decade of experience building production-ready AI systems, discrete optimization solvers, and NLP pipelines. He has led design and implementation of a state-of-the-art parallel discrete optimization solver (ddo), prototyped agentic RAG pipelines and automated metadata extraction for historical documents, and moved research into practical infrastructure and prototypes. Comfortable across the full stack, he pairs rigorous algorithmic expertise—especially in discrete optimization and document/vision models—with hands-on architecture, CI practices, and mentoring of students and teams. Now at Luminus, he focuses on strategic AI architecture and scaling solutions, while his background in system administration, academic research, and enterprise projects gives him a rare blend of operational and theoretical strengths. Notably, he has repeatedly translated deep research (e.g., worker dispatch optimization and SAT community-structure studies) into pragmatic tools and supervised many graduating projects to production-quality results.
11 years of coding experience
12 years of employment as a software developer
Bachelor, Computer Science, Bachelor, Computer Science at Haute Ecole 'Léonard de Vinci', Bruxelles
Juniper Switching, Juniper Switching at Technobel
XSLT, XSLT at Abis consulting
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Université catholique de Louvain
Sumerschool on SAT/SMT Checking and Symbolic Computation, Sumerschool on SAT/SMT Checking and Symbolic Computation at SC-square
Contributions:10 commits, 9 pushes, 1 branch in 3 years 2 months
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