Amr Mahmoud

Dr. Amr Mahmoud is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh. His work focuses on neuromorphic computing systems, machine learning, and FPGA-based accelerators for image processing and video prediction.

• PhD in Computer Engineering, University of Pittsburgh (2019)
• MSc in Engineering Physics, Cairo University (2015)
• BSc in Electronics and Electrical Communications Engineering, Cairo University (2011)

Dr. Mahmoud’s research bridges neuromorphic computing and machine learning, particularly for biomedical and sensor applications. He designs systems leveraging memristor crossbar arrays to emulate biological neural networks, enabling energy-efficient hardware solutions for tasks like cardiac arrhythmia classification and optical sensor prediction.

His recent publications highlight advancements in memristor modeling, hybrid spiking neural networks, and hardware implementations using neuromorphic architectures. Key trends include real-time biomedical diagnostics, LSTM-based sensor prediction, and crossbar array optimization for machine learning.

Contact: AMM418@pitt.edu