Mathematical geanalogy

Souhaib Ben Taieb has joined the Department of Computer Science at University of Mons (UMONS) as Associate Professor in January 2019. He is also an Adjunct Senior Research Fellow in the Department of Econometrics and Business Statistics at Monash University in Melbourne, Australia. He is directing the Big Data and Machine Learning Lab , active in machine learning, time series analysis, probabilistic forecasting, and big data processing. At UMONS, he teaches various courses on machine learning, big data analytics and artificial intelligence.

Souhaib received a B.Sc and a M.Sc in Computer Science from the Free University of Brussels in Belgium. He also received a Ph.D. in Computer Science with a specialization in Machine learning from the same institution. His Ph.D. was funded by a Doctoral research fellowship from the Belgian National Fund for Scientific Research (F.R.S.-FNRS ). He was a postdoctoral research fellow in the Spatio-Temporal and Data Science Group at KAUST in Saudi Arabia. Before joining UMONS, for three years he was a Lecturer in the Department of Econometrics and Business Statistics at Monash University in Melbourne, Australia. Finally, He was a visiting scholar at several international institutions, including the School of Earth, Energy and Environmental Sciences at Stanford University, and the Said Business School at University of Oxford.

Souhaib has made significant research contributions at the intersection of machine learning and time series analysis. His research work has been published in many A* ranked conferences and journals in the field of machine learning and statistics, including ICML, KDD, AAAI, IEEE TNNLS and JASA. His research has been funded by the Huawei Innovation Research Program, the Australian Renewable Energy Agency, the Belgian National Fund for Scientific Research (F.R.S.-FNRS). He has received the Solvay Award for his PhD thesis, and an IEEE Power & Energy Society award. He is an Associate Editor of the International Journal on Forecasting, and was a program committe emember of top conferences in machine learning such as ICML 2020, KDD 2020 and ICLR 2021.

Recent publications

  • Xiaochun Meng, James W. Taylor, Souhaib Ben Taieb, Siran Li (2021) Scoring Functions for Multivariate Distributions and Level Sets. Abstract  pdf
  • Chiara Di , Modica Pierre Pinson, Souhaib Ben Taieb (2021) Online forecast reconciliation in wind power prediction. Electric Power Systems Research, Volume 190, 2021. Abstract DOI
  • Souhaib Ben Taieb, James W Taylor, Rob J Hyndman (2020) Hierarchical Probabilistic Forecasting of Electricity Demand with Smart Meter Data. J. American Statistical Association, 6(0), 1-17. Abstract DOI  pdf
  • D Vicendese, L Te Marvelde, PD McNair, K Whitfield, DR English, S Ben Taieb, RJ Hyndman, R Thomas (2019) Hospital characteristics, rather than surgical volume, predict length of stay following colorectal cancer surgery. Australian and New Zealand Journal of Public Health, 44: 73-82. Abstract DOI
  • Souhaib Ben Taieb and Bonsoo Koo (2019) Regularized regression for hierarchical forecasting without unbiasdness conditions. Proceedings of Knowledge Discovery and Data Mining (KDD), 2019.. Abstract Online  pdf