Mohamed Ibrahim

Research Areas

Brain-inspired computing & embodied intelligence
Embedded cyber-physical integration
Hardware-software co-design
Domain-specific architectures
VLSI design and CAD

Publications

Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture 2024 - Journal Article

Awards

ECE Department Outstanding Dissertation Award - Duke University [2019]

Council of Graduate Schools (CGS)/ProQuest Distinguished Dissertation Award - Council of Graduate Schools [2018]

DATE 2017 Best Paper Award - IEEE/ACM Conference [2017]

TUM Postdoc Mobility Award - Technical University of Munich [2017]

Appointments

Tenure-Track Assistant Professor
University of Texas at Dallas [2025–Present]

Senior Research Scientist / Faculty Member
Georgia Institute of Technology [2023–2025]

Postdoc Researcher
University of California at Berkeley [2021–2023]

Sr. SOC Design Engineer
Intel Corporation [2018–2021]

PhD Research Assistant
Duke University [2013–2018]

Research & Teaching Assistant
Ain Shams University [2011–2013]

News Articles

Generative AI can't shake its reliability problem. Some say 'neurosymbolic AI' is the answer

Our paper titled "Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture" is highlighted in this article, demonstrating the importance of neuro-symbolic intelligence and system/hardware design in this area.

Genetic Barcodes Can Ensure Authentic DNA Fingerprints

Mohamed Ibrahim, along with researchers from Duke University and NYU, propose a way of ensuring that genetic samples taken in the field for DNA fingerprinting arrive at the laboratory unaltered.

Engineering Ph.D. Graduate Receives Dissertation Award

Mohamed S. Ibrahim, a recent Ph.D. graduate in electrical and computer engineering, has received the 2018 Council of Graduate Schools (CGS)/ProQuest Distinguished Dissertation Award in Mathematics, Physical Sciences, and Engineering.