Professor Mahmoud’s work is at the intersection of machine learning and computer systems, with a focus on building reliable, high performance, and intelligent computing systems. Specifically, his work aims to make AI hardware robust, whether that is in the context of hardware faults, software errors, or application-level robustness to noise. He is particularly interested in understanding and applying the capabilities of Large Learning Model (LLM) to hardware design, leveraging the immense power of AI to build future computing systems, and ensure they are robust and achieve high performance. Email
Prior to joining MBZUAI, Professor Mahmoud was a postdoctoral fellow at Harvard University in the Architecture, Circuits, and Compilers group. He completed his Ph.D. at University of Illinois at Urbana-Champaign (UIUC) under the guidance of Dr. Sarita Adve in the RSim Research Group. During his graduate studies, Professor Mahmoud was the recipient of the Mavis Future Faculty Fellowship, invited to the 7th Heidelberg Laureate Forum, and received multiple awards for teaching and mentoring undergraduate students. Prior to UIUC, Professor Mahmoud completed his BSE from Princeton University, where he was the recipient of the John Ogden Bigelow Jr. Prize in Electrical Engineering. He is on the steering committee of the Computer Architecture Student Association (CASA), the Computer Architecture Long Term Mentoring (CALM) program, the Fatima Fellowship, and an organizer of the uArch workshop; all initiatives aimed at broadening participation and providing mentorship opportunity for students in the computer systems and machine learning communities.
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