Abdulrahman Mahmoud

Assistant Professor of Computer Science

Research interests

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.

  • Postdoctoral Fellow, Harvard University.
  • Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign.
  • Bachelor of Science in Electrical Engineering from Princeton University.
  • Dean’s Award for Outstanding Senior Thesis, Advisor, Harvard University, 2022.
  • Meta Silent Data Corruptions at Scale RfP Grant – finalist.
  • Inaugural Lynn Conway Research Award for Best Technical Demo, ADA Center, for PyTorchFI.
  • Mavis Future Faculty Fellowship, UIUC.
  • Invitation to attend 7th Heidelberg Laureate Forum.
  • List of Teachers Ranked as Excellent by their Students, UIUC.
  • John Ogden Bigelow Jr. Prize in Electrical Engineering, Princeton University.

  • Abdulrahman Mahmoud: “Robust AI”, Chapter 17 in Machine Learning Systems book, 2024.
  • Celine Lee, Abdulrahman Mahmoud, Michal Kurek, Simone Campanoni, David Brooks, Stephen Chong, Gu-Yeon Wei, Alexander M. Rush: “Guess & Sketch: Language Model Guided Transpilation”, ICLR, 2024.
  • Syed Talal Wasim, Kabila Haile Soboka, Abdulrahman Mahmoud, Salman Khan, David Brooks, Gu-Yeon Wei: “Hardware Resilience Properties of Text-Guided Image Classifiers”, NeurIPS, 2023.
  • Yifan Zhao, Hashim Sharif, Peter Pao-Huang, Vatsin Shah, Arun Narenthiran Sivakumar, Mateus Valverde Gasparino, Abdulrahman Mahmoud, Nathan Zhao, Sarita Adve, Girish Chowdhary, Sasa Misailovic, Vikram Adve: “ApproxCaliper: A Programmable Framework for Application-aware Neural Network Optimization”, MLSys, 2023.
  • Abdulrahman Mahmoud, Thierry Tambe, Tarek Aloui, David Brooks, and Gu-Yeon Wei: “GoldenEye: A Platform for Evaluating Emerging Numerical Data Formats in DNN Accelerators”, DSN, 2022.
  • Abdulrahman Mahmoud, Radha Venkatagiri, Khalique Ahmed, Sasa Misailovic, Darko Marinov, Christopher W. Fletcher, and Sarita V. Adve: “Minotaur: Adapting Software Testing Techniques for Hardware Errors”, ASPLOS, 2019.

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