Assistant Professor,

Department of Computer Science and Biomedical Informatics, University of Thessaly.

Papassiopoulou 2-4, GR-35100, Lamia, Greece.

Email: stasoulis (at) uth (dot) gr

Until September 2017 I have been a Lecturer (Assistant Professor) in Mathematics at the Department of Applied Mathematics, Liverpool John Moores University, UK.

Until September 2015 I have been a Post Doctoral Researcher within the Information, Complexity and Learning research group at Department of Computer Scienceand Helsinki Institute for Information Technology HIIT, University of Helsinki , Finland.

I obtained my PhD in 2013 from University of Thessaly, Greece, under the supervision of Prof. Vassilis Plagianakos. Before this, I studied Mathematics and got my MSc in Mathematics of Computation and Decision Making at the University of Patras, Greece.

News and Upcoming events:

  • I am organizing the Special Issue "Machine Learning Applied to Sensor Data Analysis" as guest editor (deadline 20 March 2021)

  • I will give an invited talk on "MACHINE LEARNING FOR INSURANCE FRAUD DETECTION" within DAMLIFD 2020 on 21 Oct 2020


I currently supervise the following PhD students:

Panagiotis Anagnostou: "Design and Implementation of User Interface for Machine Learning algorithms in Bio-medicine"

Petros Mparmpas: "Machine Learning Algorithms and Applications"

Athanasios Siouras : "Deep Learning Applications in Medical Image Analysis for Anterior cruciate ligament (ACL) graft dimensions’ prediction and knee abnormalities"

Currently Teaching:

Department of Computer Science and Biomedical Informatics, University of Thessaly.

  • (Winter Semester) Introduction to Programming (C)

  • (Winter Semester) Artificial Intelligence

  • (Summer Semester) Data Mining in Big Data

Master of Science, Computer Science and Computational Bio-medicine, University of Thessaly.

  • (Winter Semester) Data Mining in Biomedical Applications

  • (Summer Semester) Subjects of Programming (Python)


Recent developments

  • S. Tasoulis, N. Pavlidis and T. Roos, “Non Linear Dimensionality Reduction for Clustering”, Pattern Recognition, Volume 107, 2020, 107508, ISSN 0031-3203.

  • S. Georgakopoulos, S.Tasoulis, G. Mallis, A. Vrahatis, V. Plagianakos and I. Magglogiannis, “Change Detection and Convolution Neural Networks for Fall Recognition”, Neural Computing and Applications (NCAA), Springer, 2020, accepted to appear.

  • Delibasis K., Georgakopoulos S.V., Tasoulis S.K., Maglogiannis I., Plagianakos V.P. (2020) On Image Prefiltering for Skin Lesion Characterization Utilizing Deep Transfer Learning. In: Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference. EANN 2020. Proceedings of the International Neural Networks Society, vol 2. Springer, Cham

  • A. G. Vrahatis, G. N. Dimitrakopoulos, S. K. Tasoulis, S. V. Georgakopoulos and V. P. Plagianakos, "Single-cell regulatory network inference and clustering from high-dimensional sequencing data," 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, 2019, pp. 2782-2789.

  • Chantelle L. Mason, Joseph Leedale, Sotiris Tasoulis, Ian Jarman, Steven D. Webb, A systems toxicology paracetamol overdose framework: accounting for high-risk individuals, Computational Toxicology, Volume 12, 2019, 100103, ISSN 2468-1113.

Scientific Interests

-Machine Learning -Large scale Data Mining -Big Data applications

Selected publications

Past events and conferences:

"Imagination is more important than knowledge."

Albert Einstein