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Personal profile

Biography

Dr. Souhaib Ben Taieb is a Lecturer (Assistant Professor) in Statistical Machine Learning at Monash University in Melbourne, Australia. His research interests include statistical machine learning, time series analysis, probabilistic forecasting, big data processing and smart grid analytics.

He received an M.Sc and a Ph.D. in Computer Science with a specialization in Machine learning from the Free University of Brussels in Belgium. He was a postdoctoral research fellow in the Spatio-Temporal and Data Science Group at KAUST. He was a visiting scholar at several international institutions, including the School of Earth, Energy and Environmental Sciences, Stanford University, and the Said Business School, University of Oxford.

Dr. Ben Taieb has received multiple awards including an Early-Career Faculty Research grant from Monash Business School, the Solvay Awards 2015 for his PhD thesis, an IEEE Power & Energy Society Award for the Global Energy Forecasting Competition 2012, and a Doctoral research fellow grant from the Belgian National Fund for Scientific Research.

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Projects 2017 2021

Research Output 2010 2017

  • 6 Conference Paper
  • 6 Article
  • 1 Chapter (Book)
  • 1 Review Article

Coherent probabilistic forecasts for hierarchical time series

Taieb, S. B., Taylor, J. W. & Hyndman, R. J., 1 Jan 2017, Proceedings of the 34th International Conference on Machine Learning. Precup, D. & Teh, Y. W. (eds.). Massachusetts USA: Proceedings of Machine Learning Research (PMLR), p. 3348-3357 10 p. (Proceedings of Machine Learning Research; vol. 70).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Regularization in hierarchical time series forecasting with application to electricity smart meter data

Ben Taieb, S., Yu, J., Barreto, M. N. & Rajagopal, R., 2017, Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17). Singh, S. & Markovitch, S. (eds.). Palto Alto CA USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 4474-4480 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access

A bias and variance analysis for multistep-ahead time series forecasting

Ben Taieb, S. & Atiya, A. F., 1 Jan 2016, In : IEEE Transactions on Neural Networks and Learning Systems. 27, 1, p. 62-76 15 p., 7064712.

Research output: Contribution to journalArticleResearchpeer-review

Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression

Ben Taieb, S., Huser, R., Hyndman, R. J. & Genton, M. G., 1 Sep 2016, In : IEEE Transactions on Smart Grid. 7, 5, p. 2448-2455 8 p., 7423794.

Research output: Contribution to journalArticleResearchpeer-review

Sparse and smooth adjustments for coherent forecasts in temporal aggregation of time series

Ben Taieb, S., 2016, NIPS 2016 Time Series Workshop, 09 December 2016, Barcelona, Spain. Anava, O., Khaleghi, A., Cuturi, M., Kuznetsov, V. & Rakhlin, A. (eds.). USA: Proceedings of Machine Learning Research (PMLR), Vol. 55. 11 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access