معرفی
Gilles Audemard is a Professor at Artois University in France, specializing in satisfiability (SAT), constraint satisfaction problems, and eXplainable AI (XAI). His research focuses on developing efficient solvers such as Glucose and CoSoCo, and tools like PyXAI for interpretable machine learning. He leads the XCSP3 format for combinatorial problem representation and the SAT Heritage project to archive SAT solvers.
Key achievements include the 2023 Skolem Award for influential work on hybrid SAT solving, a 2021 CAV Award for foundational contributions to SMT, and multiple best paper awards. His solvers have won medals in SAT and XCSP competitions. Audemard collaborates on projects like the French ANR-funded EXPECTATION AI Chair and contributes to open-source tools like pFactory and PyCSP3.
Research spans formal methods, constraint programming, and AI explainability, with a focus on practical applications in combinatorial optimization and machine learning interpretability. His work bridges theoretical advancements with scalable solver implementations, impacting both academic and industrial problem-solving.
