Francesco Orabona
- Associate Professor, Computer Science
- Principal Investigator, Adaptive Machine Learning
Achieving "parameter-free" machine learning is the primary focus of Professor Francesco Orabona. He is particularly interested in designing superior algorithms to train deep learning models.
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.
Awards and Distinctions
- NSF CAREER Award, National Science Foundation (NSF), 2021
- Google Research Award, Google Research, 2017
- Best Paper Award, The International Conference on Image Analysis and Processing, 2015
- Best Paper Award, The International Workshop on Attention and Performance in Computational Vision, 2005
Education
- Doctor of Philosophy (Ph.D.)
- Electrical Engineering, University of Genoa, Italy, 2007
- Laurea (BSc and MSc)
- Electrical Engineering, University of Naples "Federico II", Italy, 2003
Quote
I think I always wanted to be a researcher! Some people like to create through paint or music. Instead, I like to create through mathematics.
Research Achievements
- Area chair for the conferences Conference on Neural Information Processing Systems (NeurIPS), International Conference on Machine Learning (ICML), the Conference on Learning Theory (COLT), the International Conference on Algorithmic Learning Theory (ALT), and the International Conference on Learning Representations (ICLR).
- Associate editor of the IEEE Transactions on Information Theory since 2022.
- Action editor of the Journal of Machine Learning Research since 2020.
- Co-Chair of the 34th International Conference on Algorithmic Learning Theory.
Questions and Answers
Why KAUST?
I am very excited to join KAUST! I believe it is a fantastic opportunity for me to work with amazing scientists in a truly multicultural environment. The next few years will be pivotal in the research on artificial intelligence and I believe that being in the right place can make a huge difference.