When I was younger, I tended to be protective of my ideas, but now I believe that sharing ideas is a tremendously powerful way to improve them, ultimately leading to consistently better research work.

Education and early career

Professor Filippone received his Master’s in Physics and a Ph.D. in Computer Science from the University of Genova, Italy, in 2004 and 2008, respectively. During his Ph.D. studies in 2007, Filippone spent a year as a research scholar at George Mason University, U.S.

From 2008 to 2011, he was a research associate at the University of Sheffield, U.K. (2008 to 2009), the University of Glasgow, U.K. (2010), and University College London, U.K. (2011). In 2011, Filippone took up a lecturer position at the University of Glasgow, which he left in 2015 to join EURECOM, France, as an associate professor.

In 2024, Filippone joined the Statistics program at KAUST as an associate professor.

Areas of expertise and current scientific interests

Professor Filippone’s primary focus is Bayesian statistics, which enables sound decision-making through uncertainty quantification in model parameters and predictions; his main interests are in models based on deep learning and Gaussian processes.

Filippone is interested in the foundations of Bayesian statistics and computational aspects related to its use in practice. More specifically, he is developing approximations that enable recover tractability while being principled, practical and scalable.

He is also interested in applications in life and environmental sciences where uncertainty matters.

Editorial activities

  • Senior Area Chair for the International Conference on Artificial Intelligence and Statistics (AISTATS) (since 2023) and Area Chair (2020).
  • Guest Editor for the ECML/PKDD Machine Learning Journal track (2020).
  • Program Committee Member of NeurIPS (since 2014) and ICML (since 2015).
  • Associate Editor for Pattern Recognition (2012–2016).
  • Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems (2013–2016).
  • Technical Program Chair for the 2014 International Joint Conference on Neural Networks (IJCNN).

Career recognitions

  • Best Ph.D. Student Thesis Award from the Doctoral School of Sorbonne University, France (2023). 
  • The Biennial Pattern Recognition Journal Award 2008: M. Filippone, F. Camastra, F. Masulli, and S. Rovetta. "A survey of kernel and spectral methods for clustering." Pattern Recognition, 41(1):176-190, (January 2008).

Manuscripts published in volume 41 (2008) were judged by the journal's Editors-in-Chief and members of the Editorial and Advisory Boards based on the following criteria: “originality of the contribution, presentation and exposition of the manuscript, and citations by other researchers.”

Why KAUST?

KAUST has a unique concentration of talents, and it offers an unparalleled level of support to its faculty. I feel privileged and honored to have the opportunity to work in such a wonderful environment and to contribute to its excellence in research and teaching.