MSc
Biosketch
Muhammad ElMahdy is a Master’s student in informatics at the Technical University of Munich (TUM) and a relAI scholar at the Konrad Zuse School of Excellence in Reliable AI (relAI). He earned his Bachelor’s degree in Computer Engineering with a concentration in Artificial Intelligence and a minor in Mathematics from the American University in Cairo (AUC), graduating with Highest Honors (Summa Cum Laude).
During his studies, Muhammad conducted research in multiple domains like reinforcement learning, optimization, explainable AI, and AI for health care. He is a first author and a presenter of a paper at the ACM SIGSPATIAL 2024 conference in Atlanta, USA, where he was a finalist in the Student Research competition. He gained research experience at the AUC Wireless Research Centre, the AUC Data Science Hub and Magdi Yacoub Heart Foundation. He also gained industry experience at Barclays UK.
relAI Research
Muhammad has conducted research across multiple domains of artificial intelligence. His early work applied explainable AI to mobile and pervasive computing, for which he was selected as a finalist in the ACM SIGSPATIAL 2024 Student Research Competition. He later explored AI applications in healthcare and, subsequently, investigated reinforcement learning approaches for complex scheduling problems. His current research interests lie in generative AI, generative vision, diffusion models, causal AI, reinforcement learning and representation learning, with a strong focus on their theoretical and mathematical foundations.