Souhaib Ben Taieb is an Associate Professor of Machine Learning at the University of Mons (UMONS) in Belgium, where he leads the Big Data and Machine Learning Lab . His research spans machine learning, artificial intelligence, time series forecasting, uncertainty quantification, temporal point processes, and anomaly detection.

Previously, he served as a Lecturer in the Department of Econometrics and Business Statistics at Monash University in Australia. Souhaib holds a B.Sc and M.Sc in Computer Science from the Free University of Brussels (ULB) and earned his Ph.D. specializing in machine learning from ULB under the supervision of Prof. Gianluca Bontempi (ULB) and Prof. Rob Hyndman (Monash University), supported by a Doctoral research fellowship from the Belgian National Fund for Scientific Research. He worked as a postdoctoral research fellow in the Spatio-Temporal and Data Science Group at KAUST under the supervision of Prof. Marc G. Genton . Souhaib received the Solvay Award for his Ph.D. thesis, and he has successfully obtained various research grants both within academia and in collaboration with industry. He is an Associate Editor of the International Journal on Forecasting and serves as a reviewer for esteemed machine learning conferences such as NeurIPS, ICML, ICLR, AISTATS, and KDD.

Recent publications

  • Sukanya Patra, Nicolas Sournac, Souhaib Ben Taieb (2024) Detecting Abnormal Operations in Concentrated Solar Power Plants from Irregular Sequences of Thermal Images. Abstract
  • Tanguy Bosser, Souhaib Ben Taieb (2024) A Unifying Framework for Independent Training of Time and Mark Predictive Distributions in Neural Marked Temporal Point Processes. Abstract
  • Victor Dheur, Souhaib Ben Taieb (2024) Probabilistic Calibration by Design for Neural Network Regression. Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS) 2024.. Abstract
  • Le Thi Khanh Hien, Sukanya Patra, Souhaib Ben Taieb (2024) Anomaly detection with semi-supervised classification based on risk estimators. 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. Submitted to the Machine Learning Journal. Abstract Arxiv