Souhaib Ben Taieb is an Associate Professor at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, United Arab Emirates. His research spans artificial intelligence and statistics, including probabilistic machine learning, uncertainty quantification, model calibration, scoring rules, time series forecasting, and anomaly detection.

Previously, he was an Associate Professor of Machine Learning at the University of Mons (UMONS) in Belgium. Prior to that, he served as a Lecturer (Assistant Professor) in Business Analytics in the Department of Econometrics and Business Statistics at Monash University in Melbourne, Australia. He was also a postdoctoral research fellow in the Spatio-Temporal Statistics and Data Science group at KAUST in Saudi Arabia. Souhaib holds a Ph.D. in Computer Science (Machine Learning) from the Free University of Brussels (ULB), where he also earned his B.Sc. and M.Sc. in Computer Science.

He has secured competitive research funding from both academic institutions and industrial partners, including collaborations with Huawei, John Cockerill, and Ion Beam Applications. He received a Doctoral Research Fellowship from the Belgian National Fund for Scientific Research (FNRS) and was awarded the Solvay Award for the best Ph.D. thesis. He currently serves as an Associate Editor for the International Journal of Forecasting and regularly reviews for leading conferences and journals in machine learning and statistics.

Recent publications

  • Vincent Plassier, Alexander Fishkov, Victor Dheur, Mohsen Guizani, Souhaib Ben Taieb, Maxim Panov, Eric Moulines (2025) Rectifying Conformity Scores for Better Conditional Coverage. Proceedings of the 42th International Conference on Machine Learning (ICML), PMLR, 2025.. Abstract Arxiv
  • Victor Dheur, Matteo Fontana, Yorick Estievenart, Naomi Desobry, Souhaib Ben Taieb (2025) A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regression. Proceedings of the 42th International Conference on Machine Learning (ICML), PMLR, 2025.. Abstract Arxiv
  • Tanguy Bosser, Souhaib Ben Taieb (2024) Preventing Conflicting Gradients in Neural Marked Temporal Point Processes. Transactions on Machine Learning Research. Abstract Arxiv
  • Victor Dheur, Tanguy Bosser, Souhaib Ben Taieb (2024) Distribution-Free Conformal Joint Prediction Regions for Neural Marked Temporal Point Processes. Machine Learning. Abstract Arxiv
  • Victor Dheur, Souhaib Ben Taieb (2024) Probabilistic Calibration by Design for Neural Network Regression. Proceedings of the 27th International Conference on Artiļ¬cial Intelligence and Statistics (AISTATS) 2024.. Abstract Arxiv