Karim Tit
About Karim Tit
Karim Tit is an Industrial PhD candidate at Thales in Rennes, France, focusing on the reliability of Deep Learning networks. He has a strong academic background in Mathematics, Statistics, and Artificial Intelligence, with experience in various research and internship roles.
Work at Inria
Karim Tit has been working at Inria as a Doctorant CIFRE (Industrial PhD candidate) since 2021. His research focuses on the reliability of Deep Learning networks, specifically utilizing Rare Event simulation algorithms. This role involves both theoretical and practical aspects of his research, contributing to advancements in the field of artificial intelligence.
Current Position at Thales
Since 2021, Karim Tit has held the position of Doctorant CIFRE-defense at Thales in Rennes, Brittany, France. His work at Thales is part of an industrial doctoral program, where he collaborates with industry experts, including Louis-Marie Traonouez, to enhance the reliability of Deep Learning systems.
Education and Expertise
Karim Tit's educational background includes a Doctor of Philosophy (PhD) in Computer Science from Université de Rennes I, which he is expected to complete in 2024. He has also earned an Engineer's degree from ENSAE Paris and a Master of Research in Mathematics from PSL Research University. His studies have encompassed Mathematics, Statistics, Artificial Intelligence, and Data Science.
Previous Work Experience
Karim Tit has accumulated diverse work experience in various research and tutoring roles. He served as an Applied Math Tutor at École Polytechnique and completed internships at institutions such as KeyQuant, Centre national de la recherche scientifique, and Capital Fund Management. His experience includes quantitative research and R&D projects, contributing to his expertise in statistics and data analysis.
Research Focus
In his PhD research, Karim Tit is engaged in exploring the reliability of Deep Learning networks. He employs Rare Event simulation algorithms to address challenges in this area. His work integrates both theoretical frameworks and practical applications, aiming to improve the robustness of AI systems.