I am an Associate Professor of Statistics at KAUST, Saudi Arabia. Before joining KAUST, I held faculty positions at EURECOM (France) and at the University of Glasgow (UK). My research is at the intersection between Statistics and Machine Learning and it focuses on the mathematical and computational aspects of Bayesian statistics applied to Deep Learning and Gaussian process-based models. The motivation is that uncertainty quantification is of fundamental importance to enable sound decision making. Check out the research section for more details.
Research Highlight
Loading…
News
25-08-26 — Our new “Handbook of Bayesian Deep Learning” is now available online (link)
19-07-26 — Invited talk at the ‘SMILES summer school of machine learning’ in Nanjing University: “Bayesian Deep Learning” (link)
02-07-26 — Invited talk at the ‘Calibrated Bayes: Model Design and Adaptation Under Limited Resources’ session at ISBA in Nagoya: “Model Selection for Over-Parameterized Models” (link)
18-06-26 — Our paper “Review of timescale distributions for electrochemical impedance spectroscopy analysis: Advantages, synergies, and future directions” has been accepted for publication in the journal DeCarbon (link)
17-06-26 — Check out our new paper “DIPHINE: Diffusion-based Φ-ID Neural Estimator” (link)
30-04-26 — Our position paper “Position: agentic AI orchestration should be Bayes-consistent” has been accepted for publication at ICML 2026 (link)
09-02-26 — The KAUST Rising Stars in AI Symposium 2026 is happening this week (link)
03-02-26 — Talk at the AMCS-STAT school at KAUST: “Bayesian Deep Learning”
26-01-26 — The paper “Optimizing Data Augmentation through Bayesian Model Selection” has been accepted at ICLR 2026! (link)
22-01-26 — The paper “TENDE: Transfer Entropy Neural Diffusion Estimation” has been accepted at AISTATS 2026! (link)
27-10-25 — Participating in the workshop “Rethinking the Role of Bayesianism in the Age of Modern AI” at MBZUAI, Abu Dhabi, UAE (link)
24-10-25 — Check out our new paper “TENDE: Transfer Entropy Neural Diffusion Estimation” (link)
22-10-25 — Talk at the Huawei Lavender Summit in Chantilly, France: “Bayesian Deep Learning”
14-10-25 — Check out our new paper “Universal Adaptive Environment Discovery” (link)
08-10-25 — Check out our new paper “From Data to Rewards: a Bilevel Optimization Perspective on Maximum Likelihood Estimation” (link)