Mohamed Abdelfattah is an Assistant Professor at Cornell Tech and in the School of Electrical and Computer Engineering at Cornell University. His research interests include deep learning systems, automated machine learning, hardware-software codesign, reconfigurable computing, and FPGA architecture. Mohamed’s goal is to design the next generation of machine-learning-centric computer systems for both datacenters and mobile devices.
Mohamed received his B.Sc. from the German University in Cairo, his M.Sc. from the University of Stuttgart, and his Ph.D. from the University of Toronto. His Ph.D. was supported by the Vanier Canada Graduate Scholarship and he received three best paper awards for his work on embedded networks-on-chip for FPGAs. His Ph.D. work garnered much industrial interest and has since been adopted by multiple semiconductor companies in their latest FPGAs. After his Ph.D., Mohamed spent time at Intel’s programmable solutions group, and most recently at Samsung where he led a research team focused on hardware-aware automated machine learning.
Prof. Abdelfattah's research lies at the intersection of computer architecture and machine learning, with a special focus on reconfigurable computing. He seeks to codesign algorithms and hardware for the next generation of machine-learning-centric computer systems.
Machine learning systems, reconfigurable computing
B.Sc. (ECE) German University of Cairo, Egypt, 2009
M.Sc. (ECE) University of Stuttgart, Germany, 2011
Ph.D. (ECE) University of Toronto, Canada, 2016