Publications

Journal Papers 

1. P. Anagnostou, S. Tasoulis, A. G. Vrahatis, S. Georgakopoulos, M. Prina, J. L. Ayuso-Mateos, J. Bickenbach, I. Bayes-Marin, F. F. Caballero, L. Egea-Cortés, E. García-Esquinas, M. Leonardi, S. Scherbov, A. Tamosiunas, A. Galas, J. M. Haro, A. Sanchez-Niubo, V. Plagianakos & D. Panagiotakos (2021) Enhancing the Human Health Status Prediction: The ATHLOS Project, Applied Artificial Intelligence.

2. Lampropoulos, I.C., Raptis, D.G., Daniil, Z. et al. Temporal trends in pulmonary embolism prevalence in Greece during 2013–2017. BMC Public Health 21, 559 (2021).

3. A. Anastou, K. Delibasis, A. Boulogeorgos, H. Sandalidis, A. Vavoulas and S. Tasoulis, "A Low Complexity Indoor Visible Light Positioning Method," in IEEE Access, vol. 9, pp. 57658-57673, 2021

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

5. Georgakopoulos, S.V., Tasoulis, S.K., Mallis, G.I. et al. Change detection and convolution neural networks for fall recognition. Neural Comput & Applic 32, 17245–17258 (2020).

6. Vrahatis, A.G.; Tasoulis, S.K.; Georgakopoulos, S.V.; Plagianakos, V.P. Ensemble Classification through Random Projections for Single-Cell RNA-Seq Data. Information 2020, 11, 502

7. 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. 

8. C. Mason, J. Leedale, S. Tasoulis, I. Jarman, D. Antoine, S. Webb, “A systems toxicology approach to identifying paracetamol overdose”, CPT: Pharmacometrics & Systems Pharmacology, Vol. 7 no. 6, pp. 394–403, 2018.

9. N. Pavlidis, D. Hofmeyr, and S.Tasoulis, “Minimum density hyperplanes”, Journal of Machine Learning Research, vol. 17, no. 156, pp. 1–33, 2016.

10. L. Wang, S. Tasoulis, T. Roos and J. Kangasharju, “Kvasir: Scalable Provision of Semantically Relevant Web Content on Big Data Framework,” IEEE Transactions on Big Data, Special Issue on Big Data Analytics and the Web, vol. 2, no. 3, pp. 219–233, 2016.

11. I. Maglogiannis, S Georgakopoulos, S. Tasoulis and V. Plagianakos, “A Software Tool for the Automatic Detection and Quantification of Fibrotic Tissues in Microscopy Images,” Information Sciences, vol. 308, pp. 125–139, 2015.

12. S. Tasoulis, I. Maglogiannis, and V. Plagianakos, “Fractal analysis and fuzzy c-means clustering for quantification of fibrotic microscopy images,” Artificial Intelligence Review (AIRE), pp.1–17, 2013.

13. S. Tasoulis, C. Doukas, V. Plagianakos, and I. Maglogiannis, “Statistical data mining of streaming motion data for activity and fall recognition in assistive environments,” Neurocomputing, vol. 107, no. 0, pp. 87–96, 2013

14. S. Tasoulis, D. Tasoulis, and V. Plagianakos, “Random direction divisive clustering,” Pattern Recognition Letters, vol. 34, no. 2, pp. 131 – 139, 2013.

15. S. Tasoulis, D. Tasoulis, and V. Plagianakos, “Enhancing principal direction divisive clustering,” Pattern Recognition, vol. 43, no. 10, pp. 3391–3411, 2010. 

Conference Papers

1. P. Anagnostou, P. Barbas, A. Vrahatis and S. Tasoulis,  "Approximate kNN Classification for Biomedical Data," in 2020 IEEE International Conference on Big Data (Big Data), Atlanta, GA, USA, 2020 pp. 3602-3607.

2. 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

3. Vrahatis A.G., Tasoulis S.K., Maglogiannis I., Plagianakos V.P. (2020) Recent Machine Learning Approaches for Single-Cell RNA-seq Data Analysis. In: Maglogiannis I., Brahnam S., Jain L. (eds) Advanced Computational Intelligence in Healthcare-7. Studies in Computational Intelligence, vol 891. Springer, Berlin, Heidelberg [Book Chapter]

4. 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, doi: 10.1109/BigData47090.2019.9006016.

5. Vrahatis, G. Dimitrakopoulos, S. Tasoulis and V. Plagianakos, "Enhancing Clustering of Single-Cell RNA-Seq Data by Proximity Learning on Random Projected Spaces," 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE), Athens, Greece, 2019, pp. 846-849, doi: 10.1109/BIBE.2019.00157.

6. G. Vrahatis, G. N. Dimitrakopoulos, S. K. Tasoulis and V. P. Plagianakos, "A single-cell Systems Biology approach for disease-specific subpathway extraction," 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Siena, Italy, 2019, pp. 1-7, doi: 10.1109/CIBCB.2019.8791460.

7. G. Vrahatis, S. K. Tasoulis, G. N. Dimitrakopoulos and V. P. Plagianakos, "Visualizing High-Dimensional Single-Cell RNA-seq Data via Random Projections and Geodesic Distances," 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Siena, Italy, 2019, pp. 1-6, doi: 10.1109/CIBCB.2019.8791482.

8. Georgakopoulos S.V., Tasoulis S.K., Vrahatis A.G., Plagianakos V.P. (2020) Convolutional Neural Networks for Twitter Text Toxicity Analysis. In: Oneto L., Navarin N., Sperduti A., Anguita D. (eds) Recent Advances in Big Data and Deep Learning. INNSBDDL 2019. Proceedings of the International Neural Networks Society, vol 1. Springer, Cham  

9. Sotiris K Tasoulis, Georgios I Mallis, Spiros V Georgakopoulos, Aristidis G Vrahatis, Vassilis P Plagianakos, Ilias G Maglogiannis. “Deep Learning and Change Detection for Fall Recognition”, 2019 International Conference on Engineering Applications of Neural Networks, 262-273

10. S. K. Tasoulis, A. G. Vrahatis, S. V. Georgakopoulos and V. P. Plagianakos, "Visualizing High-dimensional single-cell RNA-sequencing data through multiple Random Projections," 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, 2018, pp. 5448-5450, doi: 10.1109/BigData.2018.8622170.  

11. S. K. Tasoulis, A. G. Vrahatis, S. V. Georgakopoulos and V. P. Plagianakos, "Biomedical Data Ensemble Classification using Random Projections," 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, 2018, pp. 166-172, doi: 10.1109/BigData.2018.8622606.  

12. S. K. Tasoulis, A. G. Vrahatis, S. V. Georgakopoulos and V. P. Plagianakos, "Real Time Sentiment Change Detection of Twitter Data Streams," 2018 Innovations in Intelligent Systems and Applications (INISTA), Thessaloniki, 2018, pp. 1-6, doi: 10.1109/INISTA.2018.8466326. 

13. V. Hyvnen, T. Pitknen, S. Tasoulis, E. Jsaari, R. Tuomainen, L. Wang, J. Corander, and T. Roos. “Fast nearest neighbor search through sparse random projections and voting,” in 2016 IEEE International Conference on Big Data (IEEE Big Data 2016), Dec 5-8, Washington DC, USA, pages 881–888. 

14. Raúl Casana-Eslava, Sotiris Tasoulis, Ian H. Jarman, Paulo J. G. Lisboa, José D. Martin-Guerrero. “Quantum clustering of high-dimensional data,” in IMA Conference on the Mathematical Challenges of Big Data, 1-2 December 2016, Mary Ward House, London, UK. (abstract submission) 

15. V. Hyvnen, T. Pitknen, S. Tasoulis, E. Jsaari, R. Tuomainen, L. Wang, J. Corander, and T. Roos. “Random Projections and Voting for Approximate Nearest Neighbor Search,” in IMA Conference on the Mathematical  Challenges of Big Data, 1-2 December 2016, Mary Ward House, London, UK. (abstract submission) 

16. Yang, S. Tasoulis and T. Ross, “Manifold Visualization via Short Walks,” in Eurovis 2016, The Eurographics Association, 6-10 June 2016, Groningen, Netherlands. 

17. S. Georgakopoulos, S. Tasoulis and V. Plagianakos, “Efficient Change Detection for High Dimensional Data Streams,” in IEEE International Conference on Big Data (IEEE BigData 2015), Oct 29, Santa Clara CA, USA, 2015, pp. 2219 - 2222. 

18. L. Wang, S. Tasoulis, T. Roos and J. Kangasharju, “Kvasir: Seamless Integration of Latent Semantic Analysis- Based Content Provision into Web Browsing,”  24th International World Wide Web Conference (WWW), 2015. 

19. S. Tasoulis, L. Cheng, N. Välimäki, N. Croucher, S. Harris, W. Hanage, T. Roos and J. Corander, “Random Projection Based Clustering for Population Genomics,” in IEEE International Conference on Big Data (IEEE BigData 2014), Oct 27-30, Washington DC, USA, 2014, pp. 675 - 682. 

20. S. Georgakopoulos, S. Tasoulis, V. Plagianakos and I. Maglogiannis, “Artificial Neural Networks and Principal Components Analysis for Detection of Idiopathic Pulmonary Fibrosis in Microscopy Images,” in 14th International Conference on Engineering Applications of Neural Networks (EANN2013). Springer Berlin Heidelberg, 2013, pp. 292–301. 

21. S. Georgakopoulos, S. Tasoulis, A. Vrahatis and V. Plagianakos. “Convolutional Neural Networks for Toxic Comment Classification,” Hellenic Conference on Artificial Intelligence (SETN 2018). 

22. S. Tasoulis, I. Maglogiannis, and V. Plagianakos, “Unsupervised detection of fibrosis in microscopy images using fractals and fuzzy c-means clustering,” in Artificial Intelligence Applications and Innovations. Springer Boston, 2012, pp. 385–394. 

23. S. Tasoulis, M. Epitropakis, V. Plagianakos, and D. Tasoulis, “Density based projection pursuit clustering,” in IEEE Congress on Evolutionary Computation (CEC). IEEE, 2012, pp. 1–8. 

24. S. Tasoulis, C. Doukas, I. Maglogiannis, and V. Plagianakos, “Independent component clustering for skin lesions characterization,” in Artificial Intelligence Applications and Innovations. Springer, 2011, pp. 472–482. 

25. S. Tasoulis, C. Doukas, I. Maglogiannis, and V. Plagianakos, “Statistical data mining of streaming motion data for fall detection in assistive environments,” in Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE. IEEE, 2011, pp. 3720–3723. 

26. S. Tasoulis, D. Tasoulis, and V. Plagianakos, “Clustering of high dimensional data streams,” in Artificial Intelligence: Theories and Applications. Springer, 2012, pp. 223–230. 

27. S. Tasoulis, V. Plagianakos, and D. Tasoulis, “Independent component divisive clustering of gene expression data,” in Eighth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics  (CIBB 2011), Gargnano-Lago di Garda, Italy, 2011. 

28. S. Tasoulis, D. Tasoulis, and V. Plagianakos, “Evolutionary principal direction divisive partitioning,” in IEEE Congress on Evolutionary Computation (CEC) . IEEE, 2010, pp. 1–7. 

29. S. Tasoulis, C. Doukas, I. Maglogiannis, and V. Plagianakos, “Skin lesions characterisation utilising clustering algorithms,” in Artificial Intelligence: Theories, Models and Applications. Springer, 2010, pp. 243–253. 

30. S. Tasoulis, C. Doukas, I. Maglogiannis, and V. Plagianakos, “Classification of apoptosis using advanced clustering techniques on digital microscopic images,” in Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. IEEE, 2010, pp. 5565–5568. 

31. S. Tasoulis, C. Doukas, I. Maglogiannis, and V. Plagianakos, “Classification of dermatological images using advanced clustering techniques,” in Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. IEEE, 2010, pp. 6721–6724. 

32. S. Tasoulis, V. Plagianakos, and D. Tasoulis, “Projection based clustering of gene expression data,” Lecture Notes in Computer Science (LNCS, volume 6160), Springer, 2009, pp. 228–239. 

33. S. Tasoulis, V. Plagianakos, and D. Tasoulis, “Projection based clustering at gene expression data,” Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2009), Genova, Italy, 2009. 

34. S. Tasoulis and D. Tasoulis, “Improving principal direction divisive clustering,” 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), Workshop on Data Mining using Matrices and Tensors, Las Vegas, USA, 2008.