Rand Asswad is a PhD candidate in applied mathematics based in Grenoble with nine years of research and teaching experience bridging mathematics, computer science, and data-driven control. His work spans robust model predictive control, bio-inspired signal reconstruction on the Heisenberg group, and mesh generation improvements—projects that led to conference publications and concrete software contributions during internships at CentraleSupélec and Inria. He has taught undergraduate science courses, implemented practical web tooling earlier in his career, and completed cross-disciplinary engineering and computer science degrees in France. Comfortable moving between theory and implementation, Rand combines a strong mathematical foundation with hands-on experimentation and algorithm engineering. An intriguing thread through his profile is applying abstract mathematical structures (e.g., Heisenberg lifts, differo-integral equations) to real-world signal and control problems, signaling a research trajectory toward robust, math-driven systems.
9 years of coding experience
Masters of Science (MSc), Theoretical and Applied Computer Science, Masters of Science (MSc), Theoretical and Applied Computer Science at Université de Rouen
Doctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at Université Grenoble Alpes
Master of Engineering (MEng), Mathematical Engineering, Master of Engineering (MEng), Mathematical Engineering at Institut national des Sciences appliquées de Rouen
Syrian Baccalaureate, 92.17%, Syrian Baccalaureate, 92.17% at Little Village School
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