Saïd Rahmani

– Research supervised by Yann Gavet and Johan Debayle – PEPR CELCER project. – Research on stochastic and dynamic modeling of degradation mechanisms in solid oxide cells (SOC). – Development of dynamic 3D stochastic geometry models and associated simulation tools (based on dynamic point processes). – Multidisciplinary collaboration with engineers, physicists, and materials scientists to solve complex problems.

– Research supervised by Johan Debayle – SMART SOLID project. – Research conducted within a multidisciplinary project with industrial partners, aiming to develop a digital twin for the understanding and control of crystallization processes. – Development of advanced image analysis methods to extract geometric descriptors from in-situ industrial video data. – Design of innovative segmentation tools based on graph theory and community detection to characterize crystal populations.

– Research supervised by Jean-François Marckert – ANR ASPAG project. – Developed a new formula for the probability that n points uniformly distributed within a convex set are in convex position. – Used this formula to prove Sylvester's conjecture for five points, contributing an advancement in stochastic geometry and probability theory.

– Led tutorials in algorithms and data structures for third-year undergraduate students in the MIAGE program.

– Taught mathematics and science to apprentices from various vocational backgrounds.

– Teaching mathematics and physics in a vocational college.

– Fixed-term contract associated to a PhD thesis. – Research concerning my PhD thesis in the following fields: Stochastic geometry, Integral geometry, Spatial statistics and Image analysis. – International mobility supported by GdR MIA/CNRS grant: ITWM Fraunhofer institute, Kaiserslautern, Germany. – Supervisor of practical work of students in the fields of: Signal processing, Image analysis and processing, Initiation to Matlab.

– Regular monitoring of 3 to 4 students per year.

– Subject: Modeling and simulation of particle aggregates using stochastic and integral geometry.