Biography
Professor Francesco Orabona is a leading researcher in parameter-free online optimization. He joined KAUST from Boston University's Department of Electrical & Computer Engineering. Orabona earned his B.Sc. and M.S. in electrical engineering in 2003 from the University of Naples "Federico II", Italy, and his Ph.D. in electrical engineering in 2007 from the University of Genoa, Italy.
Prior to joining KAUST, he held positions at several institutions including, Stony Brook University, Yahoo Research, the Toyota Technological Institute at Chicago (TTIC), the University of Milan and the Idiap Research Institute in Switzerland.
He has served as an area chair for several leading conferences, including the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), the Conference on Learning Theory (COLT) and the International Conference on Learning Representations (ICLR). Since 2022, he has been an associate editor of the IEEE Transactions on Information Theory.
Research Interests
Professor Orabona's research combines practical and theoretical machine learning approaches. His research interests encompass online learning, optimization and statistical learning theory.
In his current research, he is researching "parameter-free" machine learning algorithms that function effectively without the use of expensive hand-tuned parameters.
