20102021

Research output per year

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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

Research Output

  • 8 Conference Paper
  • 7 Article
  • 1 Chapter (Book)
  • 1 Review Article

Hospital characteristics, rather than surgical volume, predict length of stay following colorectal cancer surgery

Vicendese, D., Marvelde, L. T., McNair, P. D., Whitfield, K., English, D. R., Taieb, S. B., Hyndman, R. J. & Thomas, R., Feb 2020, In : Australian and New Zealand Journal of Public Health. 44, 1, p. 73-82 10 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File

Predicting the whole distribution with methods for depth data analysis demonstrated on a colorectal cancer treatment study

Vicendese, D., Te Marvelde, L., McNair, P. D., Whitfield, K., English, D. R., Ben Taieb, S., Hyndman, R. J. & Thomas, R., 2019, Statistics and Data Science: Research School on Statistics and Data Science, RSSDS 2019 Proceedings. Nguyen, H. (ed.). 1st ed. Singapore Singapore: Springer, p. 162-182 21 p. (Communications in Computer and Information Science; vol. 1150).

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

Open Access
File

Regularized regression for hierarchical forecasting without unbiasedness conditions

Ben Taieb, S. & Koo, B., 2019, KDD 2019: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Li, Y., Rosales, R., Terzi, E. & Karypis, G. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 1337-1347 11 p.

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

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