Publications

Journal articles

  1. Ruxandra Stoean, Nebojsa Bacanin, Catalin Stoean, Leonard Ionescu, Bridging the past and present: AI-driven 3D restoration of degraded artefacts for museum digital display, Journal of Cultural Heritage, 69, pp. 18-26, IF 3.229, 2024.
  2. Nebojsa Bacanin, Catalin Stoean, Dusan Markovic, Miodrag Zivkovic, Tarik A. Rashid, Amit Chhabra, Marko Sarac, Improving performance of extreme learning machine for classification challenges by modified firefly algorithm and validation on medical benchmark datasets, Multimedia Tools and Applications, IF 2.577, 2024. 
  3. Ruxandra Stoean, Nebojsa Bacanin, Catalin Stoean, Leonard Ionescu, Miguel Atencia, Gonzalo Joya, Computational Framework for the Evaluation of the Composition and Degradation State of Metal Heritage Assets by Deep Learning, Journal of Cultural Heritage, 64, pp.198-206, IF 3.229, 2023.
  4. Daniel Lichtblau, Catalin Stoean, Chaos Game Representation for Authorship Attribution, Artificial Intelligence, Vol. 317, pp. 103858, IF 14.05, 2023.
  5. Ana Minic, Luka Jovanovic, Nebojsa Bacanin, Catalin Stoean, Miodrag Zivkovic, Petar Spalevic, Aleksandar Petrovic, Milos Dobrojevic, Ruxandra Stoean, Applying Recurrent Neural Networks for Anomaly Detection in Electrocardiogram Sensor Data, Sensors 23, no. 24: 9878, IF 3.9, 2023. 
  6. Saravana Balaji B, Wieslaw Paja, Milos Antonijevic, Catalin Stoean, Nebojsa Bacanin, Miodrag Zivkovic, IoT Integrated Edge Platform for Secure Industrial Application with Deep Learning, Human-centric Computing and Information Sciences, Vol. 13, article number: 19, IF 6.558, 2023.
  7. Catalin Stoean, Miodrag Zivkovic, Aleksandra Bozovic, Nebojsa Bacanin, Roma Strulak-Wójcikiewicz, Milos Antonijevic, Ruxandra Stoean, Metaheuristic-Based Hyperparameter Tuning for Recurrent Deep Learning: Application to the Prediction of Solar Energy Generation, Axioms 12, no. 3: 266, IF 1.824, 2023. 
  8. Nebojsa Bacanin, Catalin Stoean, Miodrag Zivkovic, Miomir Rakic, Roma Strulak-Wójcikiewicz, and Ruxandra Stoean, On the Benefits of Using Metaheuristics in the Hyperparameter Tuning of Deep Learning Models for Energy Load Forecasting Energies 16, no. 3: 1434, IF 3.252, 2023. 
  9. Anda Ungureanu, Andreea Marcu, Ciprian Laurentiu Patru, Dan Ruican, Rodica Nagy, Ruxandra Stoean, Catalin Stoean, Dominic Gabriel Iliescu, Learning deep architectures for the Interpretation of first-trimester Fetal Echocardiography (LIFE) - a study protocol for developing an automated Intelligent Decision Support System for early fetal echocardiography, BMC Pregnancy and Childbirth, Volume 23, 20, IF 3.105, 2023.
  10. Miodrag Zivkovic, Catalin Stoean, Amit Chhabra, Nebojsa Budimirovic, Aleksandar Petrovic, and Nebojsa Bacanin, Novel Improved Salp Swarm Algorithm: An Application for Feature Selection Sensors, No. 5: 1711, IF 3.576, 2022. 
  11. Nebojsa Bacanin, Miodrag Zivkovic, Catalin Stoean, Milos Antonijevic, Stefana Janicijevic, Marko Sarac, Ivana Strumberger, Application of Natural Language Processing and Machine Learning Boosted with Swarm Intelligence for Spam Email Filtering, Mathematics Vol. 10, IF 2.258, no. 22: 4173, 2022. 
  12. Bacanin, Nebojsa, Catalin Stoean, Miodrag Zivkovic, Dijana Jovanovic, Milos Antonijevic, and Djordje Mladenovic, Multi-Swarm Algorithm for Extreme Learning Machine Optimization, Sensors 22, No. 11: 4204, 2022.
  13. Timea Bezdan, Catalin Stoean, Ahmed Al Naamany, Nebojsa Bacanin, Tarik A. Rashid, Miodrag Zivkovic, K. Venkatachalam, Hybrid Fruit-Fly Optimization Algorithm with K-Means for Text Document Clustering, Mathematics, No. 9: 1929, IF 2.258, 2021.
  14. Catalin Stoean, Daniel Lichtblau, Author Identification using Chaos Game Representation and Deep Learning, Mathematics, 8, No. 11: 1933, IF 1.747, 2020.
  15. Catalin Stoean, Ruxandra Stoean, Miguel Atencia, Moloud Abdar, Luis Velázquez-Pérez, Abbas Khosravi, Saeid Nahavandi, U. Rajendra Acharya, Gonzalo Joya, Automated Detection of Presymptomatic Conditions in Spinocerebellar Ataxia Type 2 Using Monte Carlo Dropout and Deep Neural Network Techniques with Electrooculogram Signals, Sensors, Vol. 20, No. 11, 3032, https://doi.org/10.3390/s20113032, IF 3.031, 2020.
  16. Ruxandra Stoean, Catalin Stoean, Miguel Atencia, Roberto Rodríguez-Labrada, Gonzalo Joya, Ranking Information Extracted from Uncertainty Quantification of the Prediction of a Deep Learning Model on Medical Time Series Data, Mathematics 8, No. 7: 1078, IF 1.747, 2020.
  17. Ruxandra Stoean, Catalin Stoean, Roberto Becerra-García, Rodolfo García-Bermúdez, Miguel Atencia, Francisco García-Lagos, Luis Velázquez-Pérez, Gonzalo Joya, A hybrid unsupervised—Deep learning tandem for electrooculography time series analysis. PLoS ONE 15(7): e0236401. https://doi.org/10.1371/journal.pone.0236401, IF 2.776, 2020.
  18. Shachi Mittal, Catalin Stoean, Andre A Kajdacsy-Balla, Rohit Bhargava, Digital Assessment of Stained Breast Tissue Images for Comprehensive Tumor and Microenvironment Analysis, Frontiers in Bioengineering and Biotechnology, section Bioinformatics and Computational Biology, Manuscript ID: 454225, doi: 10.3389/fbioe.2019.00246, IF 5.122, 2019.
  19. Catalin Stoean, Wieslaw Paja, Ruxandra Stoean, Adrian Sandita, Deep architectures for long-term stock price prediction with a heuristic-based strategy for trading simulations. PLOS ONE 14(10): e0223593. https://doi.org/10.1371/journal.pone.0223593, IF 2.776, 2019.
  20. Daniel Lichtblau, Catalin Stoean, Cancer diagnosis through a tandem of classifiers for digitized histopathological slides, PLOS ONE, 14(1): e0209274, IF 2.776, 2019.
  21. Cristian Mesina, Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Theodor Viorel Dumitrescu, Stelian Stefanita Mogoanta, Daniel Alin Cristian, Mihaela-Iustina Mesina-Botoran, George Mitroi, Corina-Lavinia Gruia, Maria Camelia Foarfa, Mihai Mesina, Daniela Ciobanu, Immunohistochemical evaluation of tumor budding in colorectal cancer: an important parameter with prognostic value, Romanian Journal of Morphology and Embryology, IF. 1.5, Vol. 60, No. 3, pp. 841-846, 2019.
  22. Adriana Samide, Ruxandra Stoean, Catalin Stoean, Bogdan Tutunaru, Roxana Grecu, Nicoleta Cioatera, Investigation of Polymer Coatings Formed by Polyvinyl Alcohol and Silver Nanoparticles on Copper Surface in Acid Medium by Means of Deep Convolutional Neural Networks, Coatings, Vol. 9, No. 2, Art. No. 105, 10.3390/coatings9020105, IF 2.33, 2019.
  23. Adriana Samide, Catalin Stoean, Ruxandra Stoean, Surface study of inhibitor films formed by polyvinyl alcohol and silver nanoparticles on stainless steel in hydrochloric acid solution using Convolutional Neural Networks, Applied Surface Science, Vol. 475, pp. 1-5, IF 5.155, 2019.
  24. Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Cristian Mesina, Corina Lavinia Gruia, Daniela Ciobanu, How Much and Where to Use Manual Guidance in the Computational Detection of Contours for Histopathological Images?, Soft Computing, https://doi.org/10.1007/s00500-018-3029-9, IF 2.784, Vol. 23, No. 11, pp. 3707-3722, 2019.
  25. Cristian Mesina, Catalin Stoean, Ruxandra Stoean, Victor Adrian Sandita, Corina Lavinia Gruia, Maria Camelia Foarfa, Luciana Teodora Rotaru, Alina Elena Ciobanu, Mihai Mesina, Veronica Calborean, Victor Gheorman, Daniela Ciobanu, Immunohistochemical Expression of Cd8, Cdx2, P53, D2-40 and Ki 67 in Colorectal Adenocarcinoma, Conventional and Malignant Colo-Rectal Polyps, Revista de Chimie, Vol. 69, No. 2, pp. 419-428, IF 1.605, 2018.
  26. Ruxandra Stoean, Catalin Stoean, Adrian Sandita, Daniela Ciobanu, Cristian Mesina, Interpreting Decision Support from Multiple Classifiers for Predicting Length of Stay in Patients with Colorectal Carcinoma, Neural Processing Letters, DOI 10.1007/s11063-017-9585-7, Vol. 46, No. 3, pp. 811-827, IF 2.591, 2017.
  27. Catalin Stoean, Ruxandra Stoean, Post-evolution of variable-length class prototypes to unlock decision making within support vector machines, Applied Soft Computing (ISI 2013 impact factor: 2.679), Elsevier, Vol. 25, pp. 159-173, ISSN 1568-4946, 2014. WoS: Q2-AIS, Q1-IF
  28. Ruxandra Stoean, Catalin Stoean, Modeling Medical Decision Making by Support Vector Machines, Explaining by Rules of Evolutionary Algorithms with Feature Selection, Expert Systems With Applications (ISI 2011 impact factor: 2.203), Elsevier, Vol. 40, No. 7, pp. 2677?2686, ISSN 0957-4174, 2013. WoS: Q2-AIS, Q1-IF, 12 citations
  29. Catalin Stoean, Ruxandra Stoean, Monica Lupsor, Horia Stefanescu, Radu Badea, Feature Selection for a Cooperative Coevolutionary Classifier in Liver Fibrosis Diagnosis, Computers in Biology and Medicine (ISI 2009 impact factor: 1.269), Elsevier, Vol. 41, Issue 4, pp. 238-246, ISSN 0010-4825, 2011.  WoS: Q3-AIS, Q3-IF, 8 citations
  30. Ruxandra Stoean, Catalin Stoean, Monica Lupsor, Horia Stefanescu, Radu Badea, Evolutionary-Driven Support Vector Machines for Determining the Degree of Liver Fibrosis in Chronic Hepatitis C, Artificial Intelligence in Medicine (ISI 2009 impact factor: 1.645), Elsevier, Vol. 51, Issue 1, pp. 53-65, 2011. WoS: Q2-AIS, Q1-IF, 12 citations
  31. Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu, Multimodal Optimization by means of a Topological Species Conservation Algorithm, IEEE Transactions on Evolutionary Computation (ISI 2009 Impact Factor: 4.589), IEEE Intelligence Computational Society, Vol. 14, Issue 6, pp. 842-864, ISSN 1089-778X, 2010. TSC2 code can be found here. WoS: Q1-AIS, Q1-IF, 37 citations
  32. Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D. Dumitrescu, Support Vector Machine Learning with an Evolutionary Engine, Journal of the Operational Research Society (ISI indexed, 2009 Impact Factor: 1.009), Palgrave Macmillan, Vol. 60, Issue 8 (August 2009), Special Issue: Data Mining and Operational Research: Techniques and Applications, Kweku-Muata Osei-Bryson and Vic J Rayward-Smith (Guest Editors), pp. 1116-1122, ISSN 0160-5682, 2009. WoS: Q3-AIS, Q3-IF, 8 citations

Books

  1. Catalin Stoean, Ruxandra Stoean, Support Vector Machines and Evolutionary Algorithms for Classification - Single or Together?, Intelligent Systems Reference Library, Springer, Vol. 69, ISBN 978-3-319-06940-1, 2014.
  2. Ruxandra Stoean, Catalin Stoean, Evolutie si inteligenta artificiala. Paradigme moderne si aplicatii, Editura Albastra - Grupul MicroInformatica, ISBN: 978-973-650-277-4, 2010.
  3. Catalin Stoean, Evolutionary Heuristics for Multimodal Optimization. Application to Data Mining, Research Center for Artificial Intelligence, Computer Science Series, Universitaria Publishing House, Craiova, 191 pages, ISBN: 978-606-510-164-7, 2008. 

Springer book chapters

  1. Ruxandra Stoean, Catalin Stoean, Adriana Samide, Gonzalo Joya, Convolutional Neural Network Learning Versus Traditional Segmentation for the Approximation of the Degree of Defective Surface in Titanium for Implantable Medical Devices, 15th International Work-Conference on Artificial Neural Networks, Advances in Computational Intelligence, https://doi.org/10.1007/978-3-030-20521-8, Springer International Publishing, 2019.
  2. Ruxandra Stoean, Catalin Stoean, Adrian Sandita, Evolutionary Regressor Selection in ARIMA Model for Stock Price Time Series Forecasting, Intelligent Decision Technologies, pp. 117-126, 2017.
  3. Stefan Postavaru, Ruxandra Stoean, Catalin Stoean, Gonzalo Joya Caparros, Adaptation of Deep Convolutional Neural Networks for Cancer Grading from Histopathological Images,  Advances in Computational Intelligence, pp. 38-49, 2017.
  4. Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Daniela Ciobanu, Cristian Mesina, Corina Lavinia Gruia, SVM-Based Cancer Grading from Histopathological Images using Morphological and Topological Features of Glands and Nuclei, Smart Innovation, Systems and Technologies, Vol. 55, Springer, ISBN 978-3-319-39344-5, pp. 145-155, 2016. The data set used in the article can be found here.
  5. Ruxandra Stoean, Catalin Stoean, Adrian Sandita, Daniela Ciobanu, Cristian Mesina, Ensemble of Classifiers for Length of Stay Prediction in Colorectal Cancer, Advances in Computational Intelligence, LNCS, Springer, ISBN 978-3-319-19257-4, Vol. 9094, pp. 444-457, 2015.
  6. Catalin Stoean, Ruxandra Stoean, Evolution of Cooperating Classification Rules with an Archiving Strategy to Underpin Collaboration, Intelligent Systems and Technologies - Methods and Applications, Springer, ISBN 978-3-642-01885-5, pp. 47-65, 2009.
  7. Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D. Dumitrescu, An Evolutionary Approximation for the Coefficients of Decision Functions within a Support Vector Machine Learning Strategy, Foundations on Computational Intelligence, Springer, 978-3-642-01082-8, 1, pp. 83-114, 2009.
  8. Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu, EA-Powered Basin Number Estimation by Means of Preservation and Exploration, Parallel Problem Solving from Nature, 5199, LNCS, ISBN 978-3-540-87699-1, pp. 569-578, 2008.

Selected conferences

  1. Alexandru Ciobanu, Nebojsa Bacanin, Tilman Sanders, Catalin Stoean, Assessing predictor influence in LSTM models for enhanced solar energy forecasting, 2024 26th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), IEEE, pp. 334–340, 2024.
  2. Ioan-Bogdan Iordache, Ana Sabina Uban, Catalin Stoean, and Liviu P. Dinu, Investigating the Relationship Between Romanian Financial News and Closing Prices from the Bucharest Stock Exchange. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 5130–5136, Marseille, France. European Language Resources Association, 2022.
  3. Catalin Stoean, Nebojsa Bacanin, Wieslaw Paja, Ruxandra Stoean, Dominic Iliescu, Ciprian Patru, Rodica Nagy, Semantic segmentation of fetal heart components in second trimester echocardiography, Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES2022, Procedia Computer Science, Vol. 207, pp. 3085-3092, 2022.
  4. Catalin Stoean, Nebojsa Bacanin, Ruxandra Stoean, Leonard Ionescu, Cristian Alecsa, Mircea Hotoleanu, Miguel Atencia, Gonzalo Joya, On Using Perceptual Loss within the U-Net Architecture for the Semantic Inpainting of Textile Artefacts with Traditional Motifs, 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC),  pp. 276-283, 2022.
  5. Catalin Stoean, Ruxandra Stoean, Mircea Hotoleanu, Dominic Gabriel Iliescu, Ciprian Patru, Rodica Nagy, An assessment of the usefulness of image pre-processing for the classification of first trimester fetal heart ultrasound using convolutional neural networks, 25th International Conference on System Theory, Control and Computing (ICSTCC), October 20-23, IEEE, pp. 242-248, 2021.
  6. Catalin Stoean, Leonardo Ionescu, Ruxandra Stoean, Marinela Boicea, Miguel Atencia and Gonzalo Joya, A Convolutional Neural Network as a Proxy for the XRF Approximation of the Chemical Composition of Archaeological Artefacts in the Presence of Inter-microscope Variability. In: Rojas I., Joya G., Català A. (eds) Advances in Computational Intelligence. IWANN 2021. Lecture Notes in Computer Science, vol 12862. Springer, Cham, 2021.
  7. Ruxandra Stoean, Leonard Ionescu, Catalin Stoean, Marinela Boicea, Miguel Atencia, Gonzalo Joya, A Deep Learning-based Surrogate for the XRF Approximation of Elemental Composition within Archaeological Artefacts before Restoration, Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES2021, Procedia Computer Science, Vol. 192, pp. 2002-2011, 2021.
  8. Ruxandra Stoean, Dominic Iliescu, Catalin Stoean, Vlad Ilie, Ciprian Patru, Mircea Hotoleanu, Rodica Nagy, Dan Ruican, Rares Trocan, Andreea Marcu, Miguel Atencia and Gonzalo Joya, Deep Learning for the Detection of Frames of Interest in Fetal Heart Assessment from First Trimester Ultrasound. In: Rojas I., Joya G., Català A. (eds) Advances in Computational Intelligence. IWANN 2021. Lecture Notes in Computer Science, vol 12861. Springer, Cham, 2021.
  9. Catalin Stoean, Daniel Lichtblau, Sentiment Analysis from Stock Market News in Romanian using Chaos Game Representation, 23rd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 252-258, December 7-10, 2021.
  10. Miodrag Zivkovic, Catalin Stoean, Aleksandar Petrovic, Nebojsa Bacanin, Ivana Strumberger, Tamara Zivkovic, A Novel Method for COVID-19 Pandemic Information Fake News Detection Based on the Arithmetic Optimization Algorithm, 23rd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 259-266, December 7-10, 2021.
  11. Catalin Stoean, Ruxandra Stoean, Roberto Antonio Becerra-García, Rodolfo García-Bermúdez, Miguel A. Atencia Ruiz, Francisco García-Lagos, Luis Velázquez Pérez, Gonzalo Joya, Unsupervised Learning as a Complement to Convolutional Neural Network Classification in the Analysis of Saccadic Eye Movement in Spino-Cerebellar Ataxia Type 2, 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, Gran Canaria, Spain pp. 26-37, 2019.
  12. Miguel A. Atencia Ruiz, Catalin Stoean, Ruxandra Stoean, Roberto Rodríguez-Labrada, Gonzalo Joya, Dynamic Clustering of Time Series with Echo State Networks, 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, Gran Canaria, Spain pp. 73-83, 2019.
  13. Shachi Mittal, Andre Balla, Luke Pfister, Catalin Stoean, Kianoush Falahkheirkhah, Rohit Bhargava, Tumor Identification and Grading on Histopathology Images Using Deep Learning, USCAP 108th Annual Meeting, Modern Pathology, Vol. 32, Supplement 2, Springer Nature, pp. 26-27, March 2019.
  14. Daniel Lichtblau, Catalin Stoean, Text Documents Encoding through Images for Authorship Attribution, 6th International Conference on Statistical Language and Speech Processing, SLSP 2018, Mons, Belgium, October 15-16, Lecture Notes in Computer Science, vol 11171, Springer, Cham. See a review of the proceedings.
  15. Ruxandra Stoean, Adriana Samide, Catalin Stoean, Deep Learning for Metal Corrosion Control: Can Convolutional Neural Networks Measure Inhibitor Efficiency?, 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2018), Timisoara, Romania, 2018, doi: 10.1109/SYNASC.2018.00065, pp. 387-393, 2018. 
  16. Catalin Stoean, Daniel Lichtblau, Classifier Result Aggregation for Automatically Grading Histopathological Images, 19th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), IEEE Computer Society, Los Alamitos, California, ISBN: 978-1-5386-2625-2, pp. 419-425, 2018.
  17. Catalin Stoean, In Search of the Optimal Set of Indicators when Classifying Histopathological Images, IEEE Post-Proceedings of the 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), Timisoara, pp. 449-455, 2016.
  18. Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Daniela Ciobanu, Cristian Mesina, Corina Lavinia Gruia, SVM-Based Cancer Grading from Histopathological Images using Morphological and Topological Features of Glands and Nuclei, 9th International KES Conference on Intelligent Interactive Multimedia: Systems and Services, Puerto de la Cruz, Tenerife, Spain, 15-17 June 2016, Intelligent Interactive Multimedia Systems and Services 2016, Vol. 55, Smart Innovation, Systems and Technologies, pp. 145-155, 2016.
  19. Ruxandra Stoean, Catalin Stoean, Adrian Sandita, Daniela Ciobanu, Cristian Mesina, Ensemble of Classifiers for Length of Stay Prediction in Colorectal Cancer, International Work-Conference on Artificial Neural Networks (IWANN 2015), Advances in Computational Intelligence, Lecture Notes in Computer Science, Springer, Volume 9094, Palma de Mallorca, Spain, 10-12 June, pp. 444-457, 2015.
  20. Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Cristian Mesina, Daniela Ciobanu, Corina Lavinia Gruia, Investigation on Parameter Effect for Semi-Automatic Contour Detection in Histopathological Image Processing, IEEE Post-Proceedings of the 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2015), IEEE Computer Society, September 21 – 24, pp. 445-452, 2015, Timisoara, Romania.
  21. Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Cristian Mesina, Corina Lavinia Gruia, Daniela Ciobanu, Evolutionary Search for An Accurate Contour Segmentation in Histopathological Images, The ACM Genetic and Evolutionary Computation Conference (GECCO 2015), GECCO Companion, Madrid, Spain, 11-15 July, pp. 1491-1492, 2015.
  22. Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Investigation of Alternative Evolutionary Prototype Generation in Medical Classification, IEEE Post-Proceedings of the 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2014), September 22 – 25, 2014, Timisoara, Romania, pp. 537-543, ISBN 978-1-4799-8447-3. 
  23. Catalin Stoean, Mike Preuss, Ruxandra Stoean, EA-based Parameter Tuning of Multimodal Optimization Performance by Means of Different Surrogate Models, The ACM Genetic and Evolutionary Computation Conference (GECCO-2013), Amsterdam, The Netherlands, GECCO-UP workshop, pp. 1063-1070, 2013.
  24. Mike Preuss, Catalin Stoean, Ruxandra Stoean, Niching Foundations: Basin Identification on Fixed-Property Generated Landscapes, The ACM Proceedings of the 13th annual conference on Genetic and evolutionary computation (GECCO-2011), Dublin, Ireland, pp. 837-844, 2011.
  25. Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu, EA-Powered Basin Number Estimation by Means of Preservation and Exploration, Parallel Problem Solving from Nature ? PPSN X, Lecture Notes in Computer Science, Springer Berlin / Heidelberg, vol. 5199, pp 569-578, 2008, ISBN 978-3-540-87699-1.
  26. Ruxandra Stoean, Catalin Stoean, D. Dumitrescu, Investigating Landscape Topology for Subpopulation Differentiation in Genetic Chromodynamics, IEEE Postproceedings, 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing - SYNASC 2008, IEEE Press, pp. 551-554, 2008.
  27. Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu, Disburdening the Species Conservation Evolutionary Algorithm of Arguing with Radii, The ACM Genetic and Evolutionary Computation Conference - GECCO 2007 (ISI proceedings), London, UK, pp. 1420 - 1427, 2007.
  28. Ruxandra Stoean, Mike Preuss, Catalin Stoean, D. Dumitrescu, Concerning the Potential of Evolutionary Support Vector Machines, The IEEE Congress on Evolutionary Computation - CEC 2007, Singapore, pp. 1436 - 1443, 2007. 
  29. Catalin Stoean, Ruxandra Stoean, Elia El-Darzi, Breast Cancer Diagnosis by Means of Cooperative Coevolution, Proceedings of the Third ACM International Conference on Intelligent Computing and Information Systems (ICICIS 2007), Police Press, Cairo, pp. 493-497, ISBN 977-237-172-3, 2007.
  30. Ruxandra Stoean, Catalin Stoean, Mike Preuss, Elia El-Darzi, D. Dumitrescu, Evolutionary Support Vector Machines for Diabetes Mellitus Diagnosis, IEEE IS 2006, Westminster, London, pp. 182-187, ISBN 1-4244-0196-8.
  31. Catalin Stoean, Mike Preuss, D. Dumitrescu, Ruxandra Stoean, Cooperative Evolution of Rules for Classification, IEEE Post-proceedings SYNASC 2006, IEEE Press, Lisa O'Conner (Ed.), Los Alamitos, CA, USA, pp. 317-322, ISBN 0-7695-2740-X, 2006.
  32. Ruxandra Stoean, Mike Preuss, D. Dumitrescu, Catalin Stoean, Evolutionary Support Vector Regression Machines, IEEE Post-proceedings SYNASC 2006, IEEE Press, Lisa O'Conner (Ed.), Los Alamitos, CA, USA, pp. 330-335, ISBN 0-7695-2740-X, 2006.
  33. Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu, Evolutionary Support Vector Machines for Spam Filtering, RoEduNet IEEE International Conference, Sibiu, Romania, 2006, pp. 261-266.
  34. Catalin Stoean, Mike Preuss, Ruxandra Gorunescu, D. Dumitrescu, Elitist Generational Genetic Chromodynamics - a New Radii-Based Evolutionary Algorithm for Multimodal Optimization, The 2005 IEEE Congress on Evolutionary Computation - CEC 2005 (ISI proceedings), Edinburgh, UK, September 2-5, 2005, pp. 1839 - 1846, ISBN 0-7803-9363-5.