Abdulrahman Mahmoud

Abdulrahman Mahmoud is an Assistant Professor of Computer Science at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, UAE. His research focuses on co-designing future ML systems for high performance, reliability, and resource allocation efficiency. Prior to MBZUAI, he was a postdoc researcher at Harvard University and completed his PhD at UIUC. He holds a BSE from Princeton University.

Education:

• PhD in Computer Science, UIUC (2016-2020)
• BSE in Electrical Engineering, Princeton University (2012)

Research interests span computer architecture, ML systems, GPU/accelerator design, and sustainable computing. He emphasizes resilience in AI systems and hardware-software co-design. Recent work includes frameworks like PyTorchFI for robustness analysis and GoldenEye for DNN accelerator evaluation.

Key contributions include over 50k downloads of PyTorchFI and publications at top venues like ICLR, NeurIPS, and IEEE TCAD. His work addresses environmental impacts of PFAS in computing systems and quantum computer performance modeling.

Awards include the Mavis Future Faculty Fellowship and Lynn Conway Research Award. He leads the ML and Systems Rising Stars program and serves on conference PCs (MICRO, ASPLOS). He mentors students via the CASA and CALM initiatives.

Labs/Teams: Organizes workshops like uArch 2023 and co-chairs events such as the Harvard Architecture Group. Active in diversity initiatives like the 3C Fellows program.