Adel Bibi

Dr Adel Bibi is a Senior Researcher in Machine Learning and Computer Vision at the Department of Engineering Science, University of Oxford. He is also a Junior Research Fellow (JRF) of Kellogg College. Prior to this role, he was a postdoctoral researcher at the same group for a year since October 2020. His research interests include computer vision, machine learning, and optimization. He has published more than 20 papers in CVPRs, ECCVs, ICCVs, and ICLRs, some of which were selected as orals and spotlights. He has been recognized as an outstanding reviewer for CVPR18, CVPR19, ICCV19, and ICLR22, and won the best paper award at the optimization and big data conference in KAUST. He served as an area chair for AAAI23.

Adel Bibi is a researcher at the University of Oxford with expertise in AI Safety, AI Security, and Machine Learning. His work explores the challenges and opportunities in ensuring the safe and secure deployment of artificial intelligence systems. Bibi's research includes the development of robust machine learning models, the analysis of language model fairness, and the investigation of continual learning and adversarial robustness. He has contributed to benchmarking datasets for object tracking and has examined the implications of open-source generative AI. His publications highlight the importance of addressing risks in AI systems while advancing the capabilities of machine learning models.