Ahmed Agiza

Ahmed Agiza is a Machine Learning Research Scientist at Meta, specializing in efficient machine learning methods for software and hardware design. He holds a PhD in Computer Science from Brown University, where he conducted research at the SCALE lab. His work focuses on multi-task learning, low-rank adaptation techniques, parameter-efficient training, and Electronic Design Automation (EDA). He has published papers at top conferences including CVPR, AAAI, and ICCAD. Prior to Meta, Ahmed co-founded CloudV, an Egyptian startup providing online chip design and testing tools, and worked at NVIDIA and Efabless. He holds a BSc in Computer Engineering from the American University in Cairo.