https://usersotiris.github.io/SotirisTasoulis/

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Contact with students: Wednesday 13:00-15:00 & Thursday 12:00-14:00

Tasoulis Sotirios

Assistant Professor

Knowledge Mining from Big Data

Research Interests

Machine Learning, Data Mining, Big Data applications

Courses

Curriculum vitae

Sotiris Tasoulis received his diploma in Mathematics in 2006 and his MSc in Mathematics of Computers and Decision Making in 2009 from University of Patras in Greece. In 2013 he received his PhD from the Department of Computer Science and Biomedical Informatics of the University of Thessaly in Greece. In the same year he joined Helsinki Institute for Information Technology (HIIT) and Department of Computer Science of the University of Helsinki in Finland as a post doctoral researcher in Knowledge Discovery in Big Data. Next in September 2015 Sotiris was assigned as Lecturer (Assistant Professor) at the Department of Applied Mathematics of Liverpool John Moores University in UK. In 2017 he joined the Department of Computer Science and Biomedical Informatics of the University of Thessaly as a Senior Post Doctoral Researcher while in June 2019 was assigned Assistant Professor in the same Department. His research focuses on the development of Statistical approaches able to cope with the central challenges associated with Data Analysis, and in particular Big Data, while his teaching concern courses on Data Mining and Artificial Intelligence. He has organized several workshops regarding advances in Big Data and have received several funding and scholarship awards on the subject. Finally, in many occasions Sotiris has collaborated with the industry as a consultant in Machine Learning applications.

Full Curriculum vitae

Selected Publications

  • Anagnostou, P., Tasoulis, S., Plagianakos, V. P., & Tasoulis, D. (2023). Hipart: Hierarchical divisive clustering toolbox. Journal of Open Source Software, 8(84), 5024.
  • Nellas, I. A., Tasoulis, S. K., Georgakopoulos, S. V., & Plagianakos, V. P. (2023). Two phase cooperative learning for supervised dimensionality reduction. Pattern Recognition, 144, 109871.
  • Anagnostou, P., Barmpas, P., Tasoulis, S. K., Georgakopoulos, S. V., & Plagianakos, V. P. (2023). Neural networks voting for projection based ensemble classifiers. In 2023 ieee international conference on big data (bigdata) (pp. 4567–4574).
  • Tasoulis, S., Pavlidis, N. G., & Roos, T. (2020). Nonlinear dimensionality reduction for clustering. Pattern Recognition, 107, 107508.
  • Nicos G. Pavlidis, S. K. T., David P. Hofmeyr. (2016). Minimum density hyperplanes. Journal of Machine Learning Research, 17(156), 1–33.
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