Fahad Shamshad is a doctoral researcher and graduate teaching assistant at MBZUAI with seven years of experience in AI safety, adversarial robustness, and multimodal learning. He has multiple first-author publications in top venues (CVPR, MICCAI, TPAMI), a filed patent on facial privacy protection, and notable wins including 1st place in the NeurIPS 2024 Watermarking Challenge. Fahad bridges rigorous research and practical deployment—designing trustworthy systems, mentoring graduate projects, and building real-time ML products such as camera-calibrated sports analytics. Based in Abu Dhabi, he combines signal-processing foundations from his electrical engineering background with cutting-edge LMM security work, and is actively seeking summer 2025 internships to apply his adversarial robustness expertise to real-world systems.
7 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at MBZUAI (Mohamed bin Zayed University of Artificial Intelligence)
Machine Learning Summer School Artificial Intelligence, Machine Learning Summer School Artificial Intelligence at University of Oxford
Machine Learning Summer School Artificial Intelligence, Machine Learning Summer School Artificial Intelligence at Skolkovo Institute of Science and Technology
Communication Systems, Communication Systems at Institute of Space Technology, Islamabad
Master's degree Electrical (Signal and Image Processing), Master's degree Electrical (Signal and Image Processing) at National University of Sciences and Technology (NUST)
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