Seferina Mavroudi
Seferina Mavroudi is a lecturer in the Department of Biological Agriculture and Food, of the
TEI of Ionian Islands and an adjunct lecturer (407/80) in the Department of Computer
Engineering and Informatics of the University of Patras, Greece. Her research interests
include computational intelligence, bioinformatics, and scientific computing.
Mavroudi graduated in 1998 from the Department of Electrical and Computer Engineering ,
School of Engineering of the Aristotles University of Thessaloniki .In 2000 she received a
Master’s degree from the European Postgraduate Program on Biomedical Engineering,
organized by the Faculty of Medicine of the University of Patras, the Faculty of Mechanical
Engineering and the Faculty of Electrical and Computer Engineering of the National
Technical University of Athens, in collaboration with more than 20 European Universities. In
the same program, in February of the year 2003 she completed her Ph.D. Thesis with title
“Development of advanced computational intelligence models for complex bioinformaticsand biosignal processing applications”. During her phd studies she visited the Bioinformatics
Center of the University of Pennsylvania as a visiting researcher.
Contact her at mavroudi@ ceid.upatras.gr.
Publications
Peer-reviewed journal papers
1. Stergios Papadimitriou, Konstantinos Terzidis, Seferina Mavroudi, Spiridon Likothanassis,
"ScalaLab: an effective scientific programming environment for the Java Platform based on
the Scala object-functional language," Computing in Science and Engineering, PrePrint,
2010,
ISSN:
1521-9615,
DOI
Bookmark:
http://doi.ieeecomputersociety.org/10.1109/MCSE.2010.77
2. Stergios Papadimitriou, Konstantinos Terzidis, Seferina Mavroudi, Spiridon Likothanassis,
"Scientific Scripting for the Java Platform with jLab," Computing in Science and
Engineering (ΙΕΕΕ Computing society) vol. 11, no. 4, pp. 50-60, July/Aug. 2009,
doi:10.1109/MCSE.2009.126
3. S. Mavroudi, S. Papadimitriou, S. Kossida, S. Likothanassis, A. Vlachou, “Computational
Methods & Algorithms for Mass-Spectrometry based Differential Proteomics”, Current
Proteomics, Vol. 4, Number 4, pp 223-234,December 2007
4. Stergios Papadimitriou, Seferina Mavroudi, Spiridon Likothanassis “Mutual Information
Clustering For Efficient Mining Of Fuzzy Association Rules With Application To Gene
Expression Data Analysis” the International Journal of Artificial Intelligence Tools, Vol.
15, No. 2 pp. 227-250, 2006
5. Andrei Dragomir, Seferina Mavroudi, , Anastasios Bezerianos, “Som-based Class
Discovery exploring the ICA-reduced features of microarray expression profiles”,
Comparative and Functional Genomics, Vol.5, pp.596-616, December 2004
6. Seferina Mavroudi, Stergios Papadimitriou, Anastasios Bezerianos, “Gene Expression
Analysis with a Dynamically extended Self-Organized Map that exploits class information”,
Bioinformatics , Vol.18, No.11, pp. 1446-1453, 2002
7. S.Papadimitriou, S.Mavroudi, L. Vladutu, A. Bezerianos, " Ischemia Detection with a Self
Organizing Map supplemented by Supervised Learning”, IEEE Transactions On Neural
Networks, Vol. 12, No. 3, p. 503-515, May 2001.
8. S. Papadimitriou, S. Mavroudi, L. Vladatu, A. Bezerianos, G. Pavlides, ‘’The Network
Self-Organizing Map for pattern classification, prediction and data mining of Large Data
Sets’’, Applied Intelligence Journal, Vol. 16, No. 3 pp. 185-203, May 2002.
9. S. Papadimitriou, S. Mavroudi, L. Vladutu, A. Bezerianos, G. Pavlides, “Radial Basis
Function Networks trained with instance based learning for Data Mining of Symbolic Data”,
Applied Intelligence Journal, Vol. 16, No. 3 pp. 223-234 (May 2002)
10. S. Papadimitriou, T. Bountis, S. Mavroudi, A. Bezerianos, “A Probabilistic Symmetric
Encryption Scheme for very fast Secure Communication based on Chaotic Systems of
Difference Equations’’, International Journal of Bifurcation & Chaos, Vol. 11, No12, p.
3107-3115, 2002
11. Stergios Papadimitriou, Konstantinos Terzidis, Seferina Mavroudi, Skarlas Lambros,
Spiridon Likothanassis “Fuzzy Rule based Classifiers from SVlearning”, WSEAS Trans on
Computers Issue 7, Vol. 4, July 2005, ISSN 1109-2750
12. Stergios Papadimitriou, Konstantinos Terzidis, Seferina Mavroudi, Skarlas Lambros,
Spiridon Likothanassis “Local fuzzy association rules discovery using a kernel map that
exploits apriori knowledge”, WSEAS Trans on Information Science and Applications,
Issue7, Vol. 2, July 2005, ISSSN 1790-0832
13. Stergios Papadimitriou, Konstantinos Terzidis, Seferina Mavroudi, Skarlas Lambros,
Spiridon Likothanassis “Discovering Interesting Fuzzy Rules using the Fuzzy Frequent
Pattern Tree” , WSEAS Trans on Information Science and Applications, Issue7, Vol. 2,
July 2005, ISSSN 1790-0832
Book Chapter
S. Papadimitriou, S. Mavroudi, A. Bezerianos “Kernel-Based Self-Organized Maps Trained
With Supervised Bias for Gene Expression Data Mining”, Intelligent Knowledge-Based
Systems, Business and Technology in the New Millennium, Volume V: Neural Networks,
Fuzzy Theory and Genetic Algorithm Techniques, Leondes, Cornelius T. (Ed.), 2004,
Springer Verlag, ISBN: 1-4020-7829-3
Peer-reviewed conference papers
1.) K. Theofilatos C., Dimitrakopoulos, A. Tsakalidis, S. Likothanassis, S. Mavroudi, “A New
Hybrid Method for Predicting Protein Interactions Using Genetic Algorithms and Extended
Kalman Filters”, accepted to the 10th IEEE International Conference on Information
Technology and Applications in Biomedicine (ITAB 2010)
2.) . Μ. Rapsomaniki, P. Zerefos, K. Theofilatos, A. Tsakalidis, S.Likothanassis, , S.
Mavroudi “A Novel Pipeline Method For The Preprocessing Of Mass Spectrometry
Proteomics Data”, accepted to the 10th IEEE International Conference on Information
Technology and Applications in Biomedicine (ITAB 2010)
3.) K. Theofilatos, D. Kleftogiannis, M. Rapsomaniki, V. Haidinis, S. Likothanassis, A.
Tsakalidis, S. Mavroudi “A novel embedded pre-miRNA classification approach for the
prediction of microRNA genes”, accepted to the 10th IEEE International Conference on
Information Technology and Applications in Biomedicine (ITAB 2010)
4. Adam Adamopoulos,Mirto Ntasi,Seferina Mavroudi, Spiros Likothanassis, Lazaros Iliadis,
George Anastassopoulos "Revealing the Structure of Childhood Abdominal Pain Data and
Supporting Diagnostic Decision Making", accepted toEANN2009, August 2009.
5. John Kontaxakis, M. Sangriotis, R. Angelopoulou, K. Plastira, N. Sgouros, S. Mavroudi
“Automatic Analysis of TUNEL assay Microscopy Images”, The 7th IEEE International
Symposium on Signal Processing and Information Technology, Biomedical Signal Processing
Session, pp 1172-1176, December 15-18, Cairo Egypt, 2007
6. S. Mavroudi, P. Katsanos, S. Papadimitriou and S. Likothanassis, “Transparent
Classification Process of Bioinformatics data With An Approximated Support Vector Fuzzy
Inference System”, The International Special Topic Conference on Information Technology
in Biomedicine (ITAB 2006), Ioannina –Epirus Greece, October 26-28, 2006
7. S. Papadimitriou , K. Terzidis S. Mavroudi, P. Katsanos, “Simple Fuzzy Rules extracted
with Support Vector Learining”, accepted to the IASTED International Conference on
Artificial Intelligence and Applications (AIA 2006), Feb. 13, 2006 Innsbruck Austria.
8. S. Mavroudi, P. Katsanos, S. Papadimitriou “Transparent Classification Process Analysis”,
accepted to the International Conference on Artificial Intelligence and Soft Computing (ASC
2006), August 28 to August 30, 2006, at Palma De Mallorca, Spain
9. A. Dragomir, S. Mavroudi and A. Bezerianos " Tumor classification using ensembles of
support vector machines and boosting", The Workshop on Genomic Signal Processing and
Statistics (GENSIPS 2004), Baltimore, Maryland, USA
10. Seferina Mavroudi, Andrei Dragomir, Stergios Papadimitriou, Anastasios Bezerianos
“Integrating Supervised and Unsupervised Learning in Self Organizing Maps for Gene
Expression Data Analysis” , ICANN/ICONIP, June 26-29, 2003, Istanbul, Turkey published
in Lecture Notes in Computer Science 2714, pp. 262-270
11. Seferina Mavroudi, Stergios Papadimitriou, Anastasios Bezerianos, "Gene Expression
Analysis By A Novel Dynamically Extendable Self-Organized Map Integrating Unsupervised
And Supervised Learning", Poster-session, RECOMB 2002, The Sixth Annual International
Conference on Research in Computational Molecular Biology, Washington, DC, April 18-21,
2002
12. Seferina Mavroudi, Stergios Papadimitriou, Anastasios Bezerianos, "Gene Expression
Data Analysis With A Novel SOM-Based Model that is dynamically extandable and Exploits
Class Information", Third European Symposium on Biomedical Engineering, Patras, 27/8 01/09, 2002
13. L. Vladutu, S. Papadimitriou, S. Mavroudi and A. Bezerianos, "Ischemia Detection using
Supervised Learning for Hierarchical Neural Networks based on Kohonen -Maps", Τhe 23rd
IEEE-EMBS Conference, Istanbul, 25-28 October 2001, Proceedings, 2, 1688-1691
14. L. Vladutu, S. Papadimitriou,, S.Mavroudi, A. Bezerianos, “Generalized RBF Networks
trained with Instance Based Training for mining Symbolic Data”, The 5 th Pacific-Asia
Conference on Knowledge Discovery and Data Mining (PAKDD-01), April 16-18, 2001,
Hong Kong, published in Lecture Notes in Artificial Intelligence, Advances in Knowledge
Discovery and Data Mining,Edts. David Cheung, Graham J. Williams, Qing Li, SpringerVerlang, pp. 587-594
15. S. Papadimitriou, A. Bezerianos, L. Vladutu, S.Mavroudi, “Detection of ischemic
episodes with a combination of supervised and unsupervised learning”, the Int. Conference
On Computational Intelligence, Slovakia, ISCI 2000, 29 August – 1 September 2000
published in "The State of the Art in Computational Intelligence",Physica-Verlag,
SPRINGER, 2000,P. Sincak, J. Vascak, V. Kvasnicka, R. Mesiar,Eds.
16. S. Papadimitriou, A. Bezerianos, L. Vladutu, S.Mavroudi, G. Pavlides, “Generalized
Radial Basis Function Neural Networks for data mining of symbolic data”, The Int.
Conference On Computational Intelligence, Slovakia, ISCI 2000, 29 August – 1 September
2000 published in "Quo Vadis Computational Intelligence", P. Sincak, J. Vascak, Editors,
Physica-Verlag, SPRINGER , 2000.
17. Stergios Papadimitriou, Seferina Mavroudi, Spiridon Likothanassis “Mutual Information
Clustering for efficient Mining of Fuzzy Association Rules with application to Gene
Expression Data Analysis”, Proceedings of the WSEAS CSCC 2005 for the 9th WSEAS
International CSCC Vouliagmeni, Athens, Greece (July 2005)
18. Stergios Papadimitriou, , Seferina Mavroudi, “The Fuzzy Frequent Pattern Tree”,
Proceedings of the WSEAS CSCC 2005 for the 9th WSEAS International CSCC
Vouliagmeni, Athens, Greece (July 2005)
19. Stergios Papadimitriou, Konstantinos Terzidis, Seferina Mavroudi, Skarlas Lambros,
Spiridon Likothanassis “Efficient and Interpretable Fuzzy Classifiers from Data with Support
Vector Learning” Proceedings of the WSEAS CSCC 2005 Journal for the 9th WSEAS
International CSCC Vouliagmeni, Athens, Greece (July 2005)
20. Stergios Papadimitriou, Konstantinos Terzidis, Seferina Mavroudi, Spiridon D.
Likothanassis “The Fuzzy Frequent Pattern Tree for Mining Large Databases”, Proceedings
of the 5th WSEAS International Conference on Soft Computing, Optimization, Simulation &
Manufacturing Systems -SOSM 2005,Cancun, Mexico, May 11-14 2005
21. Stergios Papadimitriou, Konstantinos Terzidis, Seferina Mavroudi, Spiridon D.
Likothanassis ,“Mining of Fuzzy Association Rules using a Kernel-based Self-Organized
Map for partitioning large databases”, Proceedings of the 5th WSEAS International
Conference on Soft Computing, Optimization, Simulation & Manufacturing Systems -SOSM
2005,Cancun, Mexico, May 11-14 2005
22. A. Dragomir, S. Mavroudi, A. Bezerianos. “A Boosting Based Framework for Gene
Expression Data Classification Using Support Vector Machines”, Proceedings of the
Mediterranean Conference on Medical and Biological Engineering (MEDICON 2004),
August 1-5, 2004, Naples, Italy