Summary
Adel Bibi is a Senior Researcher and PI at the University of Oxford with over a decade of experience at the intersection of computer vision, machine learning, and optimization, leading a team focused on provable robustness and scalable continual learning. He combines deep theoretical work—on certification and randomized smoothing—with practical systems for learning from distribution-shifting streams, producing highly selective conference highlights and orals across NeurIPS, ICLR, ICML, CVPR and ECCV. Beyond academia, he drives applied AI as Chief AI Officer at DESAISIV and leads agentic AI research for industry at SoftServe, bridging principled research with product-facing innovation. Notable service includes area chair roles and award-winning reviewing, and he has secured substantial collaborative funding (including a KAUST-Oxford CRG grant). Colleagues describe him as a researcher who routinely turns robustness theory into reproducible, scalable methods that push continual learning toward real-world deployment.
10 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Machine Learning and Optimization, Doctor of Philosophy - PhD Machine Learning and Optimization at KAUST (King Abdullah University of Science and Technology)
Bachelor of Science (BSc) Electrical Engineering, Bachelor of Science (BSc) Electrical Engineering at Kuwait University
English, Arabic