I've got the title of "Doctor in Science" @ National (Metsovio Polytechnic Athens) a.k.a. Technical University of Athens and University of Patras, with its Inter-University Course on Biomedical Engineering. After completion of my PhD, I went to USA at the Medical University of South Carolina, Department of Ophthalmology & Neuroscience. After that, at the end of 2005 I have joined the School of Computing in Dublin City University, Ireland, working (with the financial support offered by Science Foundation of Ireland) at an interesting project of Sign-Language Recognition, until 2009.
In 2010 & 2011 I went to a CISCO academy learning and working with Advanced Networking Tools (like ASA, Cloud Security) among others (Routers, Switches, LANs and WANs).
Since September 2012, I started collaboration with the Faculty of Automation & Computer Science, Polytechnic University of Bucharest, Romania. Over there I contributed at the design and turn-on-key delivery implementation of AmI-Lab (Ambient Intelligence Laboratory), the 1st of this type in Romania.
From 1st November 2014, I also started the design and implementation of educational software for preschool children, (age 4-7), more precisely intelligent tutors (see Conference papers C10 & C11 below).
From the beginning of 2021 (March) I am doing Advanced Data Analytics (based on Advanced Stats, AI & ML) at Ericsson.
Links to my other pages:
My Scholar Google profile : https://scholar.google.ro/citations?user=RjnwGOsAAAAJ&hl=en
My ResearchGate page: https://www.researchgate.net/profile/Liviu_Vladutu
Math Genealogy page: https://www.genealogy.math.ndsu.nodak.edu/id.php?id=231572
ORCID: orcid.org/0000-0002-3909-6738
[Twitter account] [GitHub account] [LinkedIn account]
And on social.Mastodon one can also find me as @vliviu@sigmoid.social
Current Research Interests include:
Signal and Image Digital Processing & Analysis;
Discovery of new biology-inspired paradigms in Artificial Intelligence (new topologies of ANN);
Computational Intelligence (Artificial Neural Networks, Fuzzy-Logic, Genetic Algorithms, Evolutionary Computation);
Multi-resolution analysis (Wavelets, Curvelets, Framelets, Gabor Frames ...);
Advanced Data Compression algorithms and methods;
Stable Distributions
Biomedical Engineering and Biostatistics.
THESES:
PhD: "Computational Intelligence Methods on Biomedical Signal Analysis and Data Mining in Medical Records"
work finished at the University of Athens and Medical Physics Department, School of Medicine, University of Patras, Greece (bilateral program).
M.Sc: "The European ST-T database self-organizing mapping for detection of ischemia"
work finished at the Medical Physics Department, School of Medicine, University of Patras, Greece.
1. BOOKS (B):
B1. Vladutu L., Computational Intelligence Methods on Biomedical Signal Analysis and Data Mining in Medical Records, Verlag Dr. Müller E.K. (25 Oct. 2013), ISBN-10: 3639169948, ISDM-13: 978-3639169942.
2. INTERNATIONAL REFEREED JOURNAL ARTICLES (J):
J8. "Framework for Posture and Face Recognition Using Kinect an Ambient-intelligence Method", by L. VLADUTU, C. MARIAN, published in "WSEAS Transactions on Computers" journal, 22 (2023), pp. 13-24, DOI: 10.37394/23205.2023.22.3. CODE: vliviu/AmbientIntelligencePaper
J7. "An attempt to model the relationship between MMI attenuation and engineering ground-motion parameters using artificial neural networks and genetic algorithms", by L. VLADUTU, G- Akis TSELENTIS , published in "Natural Hazards and Earth System Sciences (NHESS)" journal, 10, pp. 2527-2537, 7 December 2010. CODE: vliviu/NHESS_GeosciencePaper
J6. "Nonrigid Shape Recognition for Sign Language Understanding", by L. Vladutu, "WSEAS TRANSACTIONS on SYSTEMS" journal,Issue 12, Volume 8, December 2009, pp. 1263-1272; CODE: SignLanguageRecognition/main.py at main · vliviu/SignLanguageRecognition WIP (work in progress)
J5. "Generalized Radial Basis Function Networks Trained with Instance Based Learning for Data Mining of Symbolic Data", by L. Vladutu, Papadimitriou, S. Mavroudi and A. Bezerianos, published in "Applied Intelligence" journal, Vol. 16, No.3, May/June 2002, pp. 223-234; CODE: vliviu/GeneralizedRBF_miningSymbolicData: Generalized RBF Functions trained with IBL for Data Mining
J4. "Gene Expression Data Analysis with a dynamically expanding self-organizing map that exploits class information", by S. Mavroudi, S. Papadimitriou, L. Vladutu and A. Bezerianos, published in Bioinformatics, Volume 18, No. 11, 2002; CODE (modern implementation in Rust): vliviu/hme_toolbox_RUST
J3. "The Supervised Network Self-Organizing Map for Classification of Large Datasets" by S. Papadimitriou, L. Vladutu , S. Mavroudi, and A. Bezerianos published in "Applied Intelligence" journal, Vol. 16, No.3, May/June 2002, pp. 185-204; CODE: vliviu/UMAP-Based-Classification-with-Supervised-Network-SOM-Principles: Updated theory and code for "The Supervised Network Self-Organizing Map for Classification of Large Datasets"
J2. "Ischemia Detection with the Network Self-Organizing Map", by S. Papadimitriou, L. Vladutu, S. Mavroudi and A. Bezerianos, "IEEE Transactions on Neural Networks", Volume 12, number 3, pp. 503-515, 2001; CODE: (Rust): vliviu/hme_toolbox_RUST and in C++ vliviu/HME-Toolbox: It's a C++ implementation of Hierarchical Mixture of Experts we've used in Bioinformatics & Cardiology
J1. "Hierarchical State Space Partitioning with the Network Self-Organizing Map for the effective recognition of the ST-T Segment Change" by L. Vladutu, A. Bezerianos, S. Papadimitriou, "Medical and Biological Engineering and Computing", Vol. 38, No.4, July 2000;
3. REFEREED CONFERENCE PROCEEDINGS (C):
C11. "Neural Network Approaches for Children's Emotion Recognition in Intelligent Learning Applications", by F. Albu, D. Hagiescu, L. Vladutu and M. Puica presented at the "EDULEARN15: 7th annual International Conference on Education and New Learning Technologies", Barcelona, Spain, 6th-8th of July, 2015 (paper ID 887).
C10. "Intelligent Tutor for First Grade Children's Handwriting Application", by F. Albu, D. Hagiescu, M. Puica and L. Vladutu, at INTED2015, the 9th International Technology, Education and Development Conference which took place in Madrid (Spain), on the 2nd, 3rd and 4th of March, 2015.
C9. "Shape Recognition for Irish Sign Language Understanding", by L. Vladutu, presented at the 9th WSEAS International Conference on Simulation, Modeling and Optimization" (SMO '09)- BEST PAPER award at "Simulation, Modeling and Optimization".
C8. "On-line Neural Network Training for Automatic Ischemia Episode Detection", by D. Tassoulis, L. Vladutu , V. Plagianakos, A. Bezerianos and M. N. Vrahatis, presented at the 7th International Conference on Artificial Intelligence and Soft Computing, Zakopane, Poland, June 7-11, 2004- published by SPRINGER Verlag series, 2004 in "Lecture Notes in Artificial Intelligence", LNAI 3070, pp. 1062-1068;
C7. "Gene Expression Analysis with a Novel SOM-Based model that is dynamically extendable and exploits class information", by S.
Mavroudi, L. Vladutu, S. Papadimitriou, A. Bezerianos, presented at the 3rd European Symposium on Biomedical Engineering and Medical Physics, 27th August- 1st September 2002, University of Patras -Greece (Poster Session III).
C6. "Ischemia Detection using Supervised Learning for Hierarchical Neural Networks based on Kohonen-maps", by L. Vladutu , S. Papadimitriou, S. Mavroudi and A. Bezerianos, presented at "The 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society", Istanbul, 25-28 October 2001, [Best paper award- paper acknowledged by US Ministry of Health];
C5. "Generalised RBF Network trained using an IBL Algorithm for Mining Symbolic Data", by L. Vladutu, S. Papadimitriou, S. Mavroudi and A. Bezerianos, presented at "The Fifth Pacific-Asia Conference on Knowledge Discovery and Data Mining", 16-18 April 2001, Hong Kong;
C4. "Generalized RBF Networks trained using an IBL algorithm for mining Symbolic Data" by L. Vladutu, S. Papadimitriou, S. Mavroudi and A. Bezerianos, published by Springer-Verlag in "Lecture Notes in Artificial Intelligence" series, 2001, Volume 2035/2001, 587-593, DOI: 10.1007/3-540-45357-1_63.
C3. "Detection of Ischemic Episodes with a combination of unsupervised and supervised learning" by S. Papadimitriou, L. Vladutu, S. Mavroudi, A. Bezerianos, published in "The State of the Art in Computational Intelligence", Physica-Verlag, SPRINGER, 2000,P. Sincak, J. Vascak, V. Kvasnicka, R. Mesiar, Eds., Proceedings of the "International Symposium on Computational Intelligence", Kosice, Slovakia.
C2. "Generalized Radial-Basis Function Neural Networks for Data Mining of Symbolic Data" by S. Papadimitriou, A. Bezerianos, L. Vladutu, S. Mavroudi,G. Pavlides published in "Quo Vadis Computational Intelligence", P. Sincak, J. Vascak, Editors, SPRINGER Verlag, 2000;
C1. "Hierarchical State Space Partition with the Network Self-Organizing Map for the effective recognition of the ST-T Segment change" by L. Vladutu, A. Bezerianos, S. Papadimitriou presented at The 2nd Panhellenic Conference on Biomedical Engineering, Athens,Greece on 5-6 November 1999; Abstract: Hierarchical State Space Partitioning with the Network Self-Organizing Map for the effective recognition of the ST-T Segment Change
4. Final Observations & OTHER SCHOLARLY PUBLICATIONS (O):
O1. Most of the papers above have the Open-source code on my Github page: vliviu (Liviu Vladutu)
O2. "A Novel Method for facial recognition based on stable distributions", by Ilie Ablachim-Constantin Denis, Liviu Vladutu, Adina-Magda Florea, SSCS-2015 Students Scientific Communications Session.