Current and recent activities

• Researcher at the Frontier Development Lab (FDL), a NASA co-operative agreement with the SETI Institute- FDL 2022 EARTH SCIENCE - SMD Knowledge Graph Discovery .
• 2024: Electronic Media Chair at the Genetic and Evolutionary Computation Conference 2024 (GECCO’24) - GECCO2024 Organizers .
• 2022: Competitions Chair at the Genetic and Evolutionary Computation Conference 2022 (GECCO’22) - GECCO2022 Organizers .
• June 2021-June 2023: Head of Department of Electronics Engineering of Federal University of Technology – Paraná
• 2021: Competitions Chair at the Genetic and Evolutionary Computation Conference 2021 (GECCO’21) - GECCO2021 Organizers .
• September, 2020: Organizer of the Electronics and Industrial Automation Seminars (Semana Acadêmica de Eletrônica e Automação Industrial-SEA2020), local conference at UTFPR, Brazil – general chair.
• October, 2019: NASA International Space Apps Challenge Competition – evaluation commitee and opening speaker (Artificial Intelligence: From IoT, Industry 4.0 , Big Data To Smart Cities) - Ponta Grossa, PR, Brazil.
• September, 2019: Organizer of the Integrated Academic Week (Semana Acadêmica Integrada-SAI2019) and Electronics and Industrial Automation Seminars (Semana Acadêmica de Eletrônica e Automação Industrial- SEA2019), local conference at UTFPR, Brazil – infra-structure and technical commitee.
• July, 2019- August, 2020: Artificial Intelligence classes - lecturer – exclusively in English. This course introduces basic knowledge representation, techniques, architectures, problem solving and learning methods of artificial intelligence, used to build applied intelligent systems from a computational point of view.
• September, 2018: Visiting lecturer at the Electrical Engineering Department from at Akdeniz University, Antalya, Turkey - Graduate Program.
• March, 2018: Paper “On the performance of multi-objective estimation of distribution algorithms for combinatorial problems” shortlisted for the best paper award at IEEE Conference on Evolutionary Computation (CEC2018) in Rio de Janeiro, Brazil.
• June, 2017: Participated at the The 50 Years of the ACM Turing Award Celebration Conference in San Francisco, California. Read the newsletter here.

Research interests

• Optimization: Numerical and combinatorial optimization, multi and many optimization problems, fitness landscape analysis, modelling, optimizations with simulation;
• Evolutionary Computation: Metaheuristics, local search and extensions, genetic Programming, estimation of distribution algorithms, EA theory;
• Machine learning: Neural networks, bayesian networks, probabilistic models, surrogate models, theoretical machine learning.

Education and Degrees

• 2014-2017: Federal University of Technology – Paraná - CPGEI – Ph.D. in Computer Engineering
• 2008-2011: Federal University of Technology – Paraná - CPGEI – Master Degree in Computer Engineering;
• 2003-2006: Federal University of Technology – Paraná –Technology Degree in Industrial Automation;
• 2002-2006: State University of Ponta Grossa – Bachelor Degree in Computer Engineering;

Professional Activity

Associate Professor at the Electrical Engineering Department in Federal University of Technology – Paraná.

Head of Department of Electronics Engineering of Federal University of Technology – Paraná

Taught classes:

• Artificial Intelligence classes – exclusively in English
• Automation classes
• Programming Languages classes
• Control Systems
• Industrial Automation

Internship Coordinator:

• Company-university agreements
• Monitoring students internship plan and tasks
• Follow-up visits at students work places

Projects coordinator:

• Solving optimization problems using probabilistic models and machine learning: This project aims to develop artificial intelligence methods and computational techniques, based on mathematicals models, specially on probabilistic models, to be applied on image processing, machine learning, and optimization problems. This project has been developed with undergraduating students from UTFPR.
• Sunspot groups classification and recognition using Deep Learning: This project has been developed involving undergraduate students from UTFPR and with international cooperation with Universidad de Guadalajara (Mexico)
• Detection of COVID-19 deseases based on X-rays images - Co-coordinator. This projetct intends to develop a cloud-based application to the analysis of lung X-ray images using machine learning and deep learning techniques for classification and detection of the COVID-19 deseases. This project has been developed with international cooperation from Aalborg University, Denmark, and Mohammed V University in Rabat, Morocco.

Supervisions:

• UNSUPERVISED MODEL OF STRUCTURES SEGMENTATION IN BRAIN TOMOGRAPHY EXAMINATIONS - Phd student - co-advisor UFG
• Machine Leaning techniques as surrogate models applied to optimization algorithms - Master student UTFPR
• RNAseq machine learning approaches for breast cancer classification- Master student UTFPR
• Deep learning techniques applied to recognition for assisted vehicles - Master student UTFPR

Events Organizer and Volunteering

• Etetronic Media Chair at the Genetic and Evolutionary Computation Conference 2024 (GECCO’24) - GECCO2024 Organizers
• Young Bioinformatician Award Chair - Master and Thesis Award at the X-meeting 2023 - X-MEETING 2023
• Competitions Chair at the Genetic and Evolutionary Computation Conference 2022 (GECCO’22) - GECCO2022 Organizers
• Competitions Chair at the Genetic and Evolutionary Computation Conference 2021 (GECCO’21) - GECCO2021 Organizers
• General Coordinator/Chair of the Electronics and Industrial Automation Seminars (Semana Acadêmica de Eletrônica e Automação Industrial)-SEA2020: This event occurs every year at the UTFPR to promote academic activities and includes seminars, workshops, competitions, tutorials, and papers presentations;
• Infrastructure Coordinator of the Electronics and Industrial Automation Seminars (Semana Acadêmica de Eletrônica e Automação Industrial)-SEA2019
• Infraestructure commitee member of the Integrated Academic Week (Semana Acadêmica Integrada-SAI2019): This event is sponsored by UTFPR in partnership with some local companies and factories to promote the integration among students and sharing knowledge from different courses and universities;
• Volunteering at ACM’s Celebration of 50 Years of the Turing Award conference - 2017
• Volunteering at The Genetic and Evolutionary Computation Conference - GECCO 2016
• Volunteering at The Genetic and Evolutionary Computation Conference - GECCO 2017

Received Grants and Awards

• In 2021 was selected to be part of a NASA - National Aeronautics and Space Administration project to study the origin of the Solar Wind and the impact on Earth. The project is conducted by Frontier Development Lab (FDL), NASA and SETI Institute.
• 20-days Foreign academic activities in University of Adelaide, Australia –teaching and lectures – May 2021
• 2nd best in Theses Competition (11th edition of CTDIAC (Concurso de Teses e Dissertações em Inteligência Artificial e Computacional) during Brazilian Conference on Intelligent Systems (BRACIS 2018) in São Paulo, Brazil.
• Award of the Spotlight Doctoral Thesis at the Theses Contest during 5th IEEE Latin American Conference on Computational Intelligence (LA-CCI 2018) in Guadalajara, México.
• I have been selected to the Mevlana Exchange Program in Antalya, Turkey, during 14 days (September,2018) as a visitor lecturer at the Electrical Engineering Department from Akdeniz University, giving classes for Graduate Program.
• Association of Computing Machinery (ACM) Travel Grant to attend GECCO 2016 in Denver, Colorado, USA.
• ACM Travel Grant to attend GECCO 2017 in Berlin, Germany.
• ACM Financial support to attend the ACM’s Celebration of 50 Years of the Turing Award conference in San Francisco USA on June, 2017.

Memberships

• Member of the Education Portal Subcommittee of IEEE Computational Intelligence Society

Journal Reviewer

• IEEE Transactions on Evolutionary Computation
• Applied Soft Computing
• IEEE Transactions on Systems, Man and Cybernetics: Systems
• IEEE Latin America Transactions

Conference PC member

• IEEE Congress on Evolutionary Computation (CEC 2020)
• IEEE Congress on Evolutionary Computation (CEC 2019)
• Brazilian Conference on Intelligent Systems (BRACIS 2020)
• Brazilian Conference on Intelligent Systems (BRACIS 2021)
• XV Brazilian Congress on Computational Intelligence (CBIC 2021)
• IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI 2020)

Repositories with developed codes

• HMOBEDA : Hybrid multi-objective Bayesian estimation of distribution algorithm - Journal of Heuristics paper .
• HSEDA: Hyper-heuristic based on EDA for the TTP - GECCO 2017 paper .
• TTP-FLA: A fitness landscape analysis of the travelling thief problem - GECCO 2018 paper .
• Genetic Programming for TTP: A hyperheuristic approach based on low-level heuristics for the travelling thief problem - Genetic Programming and Evolvable Machines journal paper.
• MLON: Multi-layer local optima networks for the analysis of advanced local search-based algorithms - GECCO 2020 paper .
• MATE: Model-based Algorithm Tuning Engine - EVO*2021 paper .

External links

• Google scholar
• DBLP
• ResearchGate

Publications

Journal papers

• El Yafrani, M., Scoczynski, M., Wagner, M. et al. A regression analysis of the impact of routing and packing dependencies on the expected runtime. Soft Comput (2023). https://doi.org/10.1007/s00500-023-08402-7
• Costa, L. F., Barchi, T. M., de Morais, E. F., Coca, A. E., Schemberger, E. E., Martins, M. S., & Siqueira, H. V. (2023). Neural Networks And Ensemble Based Architectures To Automatic Musical Harmonization: A Performance Comparison. Applied Artificial Intelligence, 37(1), 2185849.
• OLIVA, DIEGO ; MARTINS, MARCELLA S. R. ; HINOJOSA, SALVADOR ; ELAZIZ, MOHAMED ABD ; DOS SANTOS, PAULO VICTOR ; DA CRUZ, GELSON ; MOUSAVIRAD, SEYED JALALEDDIN . A hyper-heuristic guided by a probabilistic graphical model for single-objective real-parameter optimization. International Journal of Machine Learning and Cybernetics, v. 1, p. 1, 2022.
• ITABORAHY FILHO, MARCO ANTONIO ; PUCHTA, ERICKSON ; MARTINS, MARCELLA S. R. ; ANTONINI ALVES, THIAGO ; TADANO, YARA DE SOUZA ; Corrêa, Fernanda Cristina ; STEVAN, SERGIO LUIZ ; SIQUEIRA, HUGO VALADARES ; KASTER, MAURICIO DOS SANTOS . Bio-Inspired Optimization Algorithms Applied to the GAPID Control of a Buck Converter. Energies, v. 15, p. 6788, 2022.
• MARTINS, MARCELLA S. R.; YAFRANI, MOHAMED EL ; DELGADO, MYRIAM ; LÜDERS, RICARDO ; SANTANA, ROBERTO ; SIQUEIRA, HUGO V. ; AKCAY, HUSEYIN G. ; AHIOD, BELAÏD . Analysis of Bayesian Network Learning Techniques for a Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm: a case study on MNK Landscape. JOURNAL OF HEURISTICS, v. 1, p. 1, 2021.
• SCOCZYNSKI, MARCELLA; DELGADO, MYRIAM ; LÜDERS, RICARDO ; OLIVA, DIEGO ; WAGNER, MARKUS ; SUNG, INKYUNG ; EL YAFRANI, MOHAMED . Saving computational budget in Bayesian network-based evolutionary algorithms. Natural Computing, v. 1, p. 1-16, 2021.
• Carolina Deina, Matheus Henrique do Amaral Prates, Carlos Henrique Rodrigues Alves, Marcella Scoczynski Ribeiro Martins, Flavio Trojan, Sergio Luiz Stevan, Hugo Valadares Siqueira, A Methodology for Coffee Price Forecasting Based on Extreme Learning Machines, Information Processing in Agriculture, 2021, ISSN 2214-3173. https://doi.org/10.1016/j.inpa.2021.07.003.
• Jakobovic D., Picek S.,Martins M.S.R., Wagner M. (2021). Toward more efficient heuristic construction of Boolean functions. Applied Soft Computing, pp.106-147.
• Scoczynski, M., Delgado, M., Lüders, R., Oliva, D., Wagner, M., Sung, I., El Yafrani, M. (2021). Saving computational budget in Bayesian network-based evolutionary algorithms. Natural Computing, 1-16.
• Martins, M. S., El Yafrani, M., Delgado, M., Lüders, R., Santana, R., Siqueira, H. V., Akcay, H. G., Ahiod, B. (2021). Analysis of Bayesian Network Learning Techniques for a Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm: a case study on MNK Landscape. Journal of Heuristics, 1-25.
• Oliva, D., Martins, M. S., Osuna-Enciso, V., de Morais, E. F. (2020). Combining information from thresholding techniques through an evolutionary Bayesian network algorithm. Applied Soft Computing, pp.106-147/
• Martins, M. S., Delgado, M. R., Lüders, R., Santana, R., Gonçalves, R. and Almeida, C. P. d., “Exploring the probabilistic graphic model of a hybrid multi-objective bayesian estimation of distribution algorithm”, Applied Soft Computing, pp. 328–343, 2018
• El Yafrani M., Martins, M. S., Wagner, M., Ahiod, B., Delgado, M., and Lüders, R. (2017). A hyperheuristic approach based on low-level heuristics for the travelling thief problem. Genetic Programming and Evolvable Machines, pages 1–30.
• Martins, M. S. R., Delgado, M. R. B. S., Lüders, R., Santana, R., Gonçalves, R. A., and Almeida, C. P. d. (2017b). Hybrid multi-objective Bayesian estimation of distribution algorithm: a comparative analysis for the multi-objective knapsack problem. Journal of Heuristics, pages 1–23.
• Martins, M. S. R., Fuchs, S.C., Pando L.U., Delgado M., and Lüders, R. (2013) PSO with path relinking for resource allocation using simulation optimization. Computers & Industrial Engineering , pages 322–330.

Conference papers

• Roelien C. Timmer, Megan Mark, Fech Scen Khoo, Marcella Scoczynski Ribeiro Martins, Anamaria Berea, Gregory Renard, and Kaylin Bugbee. 2023. NASA Science Mission Directorate Knowledge Graph Discovery. In Companion Proceedings of the ACM Web Conference 2023 (WWW '23 Companion). Association for Computing Machinery, New York, NY, USA, 795–799. https://doi.org/10.1145/3543873.3587585
• Mark, M., Khoo, F. S., Martins, M. S. R., Timmer, R. C., Berea, A., & Renard, G. (2022, December). A Knowledge Graph Connecting Multiple NASA Science Mission Directorate Domains. In AGU Fall Meeting Abstracts (Vol. 2022, pp. IN25A-01).
• Yafrani, M. E., Scoczynski, M., Delgado, M. R., Lüders, R., Nielsen, P., & Wagner, M. (2022, July). On the fitness landscapes of interdependency models in the travelling thief problem. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 188-191).
• Lamdouar, H., Sundaresan, S., Jungbluth, A., Saikia, S. B., Camarata, A. J., Miles, N., Scoczynski M., Stone, M., Sarah, A., Muñoz-Jaramillo A., Narock A., Szabo A. A. Deep-SWIM: A few-shot learning approach to classify Solar WInd Magnetic field structures. Fourth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2021).
• Camarata, A. , Lamdouar, H., Sundaresan, S., Jungbluth, A., Saikia, S. B., J., Miles, N., Scoczynski M., Stone, M., Sarah, A., Muñoz-Jaramillo A., Narock A., Szabo A. Classification of Solar Wind Discontinuities Using Supervised Machine Learning. AGU Fall Meeting 2021. 
• Stone, M., Camarata, A. , Lamdouar, H., Sundaresan, S., Jungbluth, A., Saikia, S. B., J., Miles, N., Scoczynski M., Sarah, A., Muñoz-Jaramillo A., Narock A., Szabo A. Classification of Solar Wind Structures via Unsupervised Machine Learning. AGU Fall Meeting 2021. 
• Thiago Fellipe Ortiz de Camargo, Paulo Victor dos Santos, Sthefanie Monica Premebida, Guilherme Alberto Sousa Ribeiro, ...& Marcella Scoczynski. A practical Deep Learning approach to assist COVID-19 detection based on Chest X-ray images. 2021 IEEE LA-CCI paper
• Scoczynski, M., Oliva, D., Rodríguez-Esparza, E., Delgado, M., Lüders, R., Yafrani, M. E., ... & Peréz-Cisnero, M. (2021, July). A selection hyperheuristic guided by Thompson sampling for numerical optimization. In  Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1394-1402). https://doi.org/10.1145/3449726.3463140
• Corrêa, F. C., Eckert, J. J., Santiciolli, F. M., Martins, M. S. R., Gonçalves, C., Baroncini, V. H. V., ... & Dedini, F. G. (2021). Power Management Strategies for Hybrid Vehicles: A Comparative Study. In Applications of Computational Intelligence: Third IEEE Colombian Conference, ColCACI 2020, Cali, Colombia, August 7-8, 2020, Revised Selected Papers 3 (pp. 103-116). Springer International Publishing.
• Marcella S. R. Martins, Mohamed El Yafrani, Myriam R. B. S. Delgado, and Ricardo Lüders. 2020. "Multi-layer local optima networks for the analysis of advanced local search-based algorithms". In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO ’20). Association for Computing Machinery, New York, NY, USA, 219–227. DOI:https://doi.org/10.1145/3377930.3390179
• Corrêa, F. C., Eckert, J. J., Silva, L. C., Martins, M., Baroncini, V., Santiciolli, F. M., ... & Dedini, F. G. (2020, August). Rule-based Control and Fuzzy Control for Power Management Strategies for Hybrid Vehicles. In 2020 IEEE Colombian Conference on Applications of Computational Intelligence (IEEE ColCACI 2020) (pp. 1-6). IEEE.
• Durasevic, M., Jakobovic, D., Martins, M. S. R., Picek, S., & Wagner, M. (2020). "Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations". arXiv preprint arXiv:2004.12762. Accepted in PPSN2020.
• Oliva, D., Rodriguez-Esparza E., Martins, M. S., Elaziz M. A., Hinojosa S., Ewees A. A., Lu S. Balancing the Influence of Evolutionary Operators for Global Optimization. In: 2020 IEEE Congress on Evolutionary Computation (CEC), 2020, Glaskow. 2020 IEEE Congress on Evolutionary Computation (CEC), 2020.
• El Yafrani, M., Scoczynski, M., Delgado, M., Lüders, R., Sung, I., Wagner, M., & Oliva, D. (2019, October). On updating probabilistic graphical models in Bayesian Optimisation Algorithm. In 2019 8th Brazilian Conference on Intelligent Systems (BRACIS) (pp. 311-316).
• Premebida S., Pechebovicz D., Camargo T., Nazário H., Soares V., Baroncini V., Morais E. de, Siqueira H., Oliva D., Martins M. S. R. “Sunspot behavior forecast using neural networks approaches”. IEEE 2020 International Conference on Industrial Technology, ICIT, 2020
• Pechebovicz D., Premebida S., Soares V., Camargo T., Bittencourt J., Baroncini V., Martins M.. “Plants recognition using embedded Convolutional Neural Networks on Mobile devices”. IEEE 2020 International Conference on Industrial Technology, ICIT, 2020.
• Deina C. ; Prates M. H. A.; Alves C. H. R.; Martins M. S. R. ET AL. Comparação do desempenho entre modelos lineares e redes neurais para previsão do preço do café. In: LI Simpósio Brasileiro De Pesquisa Operacional, 2019, Limeira. Anais eletrônicos. Campinas, Galoá, 2019.
• Oliva D., Hinojosa S., Martins M. S. R., Rodriguez-Esparza E., Ortega-Sanchez N. and Pérez-Cisneros M. “Improving the estimation of parameters in induction motors using an evolutionary computation algorithm”. 2019 IEEE LA-CCI paper
• Jakobovic, D., Picek, S., Martins, M. S. R., Wagner, M. “A characterisation of S-box fitness landscapes in cryptography”. In: the Genetic and Evolutionary Computation Conference, 2019, Prague. Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '19. New York: ACM Press, 2019. p. 285.
• Oliva, D., Martins, M. S. R. “A Bayesian based Hyper-Heuristic approach for global optimization”. In: 2019 IEEE Congress on Evolutionary Computation (CEC), 2019, Wellington. 2019 IEEE Congress on Evolutionary Computation (CEC), 2019. p. 1766
• Camargo, T. , Pechebovicz, D., Premebida, S. M. ; Soares, V. R., Baroncini, V., Siqueira, H. ; Oliva, D., Martins, M. “Detecting a predefined solar spot group with a pretrained convolutional neural network”. In: 2019 IEEE Colombian Conference on Applications in Computational Intelligence (ColCACI), 2019, Barranquilla. 2019 IEEE Colombian Conference on Applications in Computational Intelligence (ColCACI), 2019. p. 1.
• Martins, M. S., El Yafrani M., Santana R., Delgado M. R., Luders R., and Ahiod B., “On the performance of multi-objective estimation of distribution algorithms for combinatorial problems”, In IEEE Conference on Evolutionary Computation, ser. CEC’18, 2018, pp. 1–8 in arXiv:1806.09 935. _Nominated for best paper_
• El Yafrani, M., Martins, M. S., Krari, M. El, Wagner, M., Delgado M. R., Ahiod B., and Lüders R., “A fitness landscape analysis of the travelling thief problem”, In Proceedings of the Genetic and Evolutionary Computation Conference, ser. GECCO’18, 2018, pp. 277–284.
• Soares, Vinícios, Luz, Mathias L., Ribeiro, A. H., Ribeiro, Rafael S., Martins, M. S., Santos, Max. M. D., Mira, Joaquim. “On the Applicability of Deep Learning for Road Signal Recognition”. In 13th IEEE/IAS International Conference on Industry Applications, ser. INDUSCON 2018.
• Borges, F. G., Monteiro L. F., Martins, M. S. R., Correa, F. C., Siqueira H., Kaster, M. “Performance Comparison of Particle Swarm Optimization Strategies to Adjust a Nonlinear GAPID Controller ”. In 13th IEEE/IAS International Conference on Industry Applications, ser. INDUSCON 2018.
• Martins, M. S., Delgado, M. R., Lüders, R., Santana, R., Gonçalves, R. and Almeida, C. P. d. (2017a). Probabilistic Analysis of Pareto Front Approximation for a Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm. In Proceedings of the 2017 Brazilian Conference on Intelligent Systems, BRACIS’17, pages 384–389.
• Martins, M. S., Delgado, M. R., Santana, R., Lüders, R., Gonçalves, R. A., and Almeida, C. P. d. (2016). HMOBEDA: Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO’16, pages 357–364, New York, NY, USA. ACM.
• Martins, M. S. R., El Yafrani, M., Delgado, M. R. B. S., Wagner, M., Ahiod, B., and Lüders, R. (2017c). HSEDA: A heuristic selection approach based on estimation of distribution algorithm for the travelling thief problem. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO’17, pages 361–368, New York, NY, USA. ACM.
• Martins, M. S. R., Delgado M., and Lüders, R. (2009). Análise da Otimização com Simulação da Transferência de Petróleo. In Proceedings of the Simpósio Brasileiro de Pesquisa Operacional, XLI SBPO, 2009.
• Martins, M. S. R., Delgado M., and Lüders, R. (2009). Discrete Event Simulation for Petroleum Transfers involving harbors, refineries and pipelines. Rio Pipeline.

Book chapters

• Khoo, F. S., Mark, M., Timmer, R. C., Martins, M. S. R., Foshee, E., Bugbee, K., ... & Berea, A. (2023, June). Building Knowledge Graphs in Heliophysics and Astrophysics. In International Conference on Applications of Natural Language to Information Systems (pp. 215-228). Cham: Springer Nature Switzerland.
• Corrêa, Fernanda Cristina ; Eckert, Jony Javorski ; Santiciolli, Fabio Mazzariol ; MARTINS, MARCELLA SCOCZYNSKI RIBEIRO ; Gonçalves, Cristhiane ; Baroncini, Virgínia Helena Varoto ; Alckmin e Silva, Ludmila ; Dedini, Franco Giuseppe . Power Management Strategies for Hybrid Vehicles: A Comparative Study. Communications in Computer and Information Science. 1ed.: Springer International Publishing, 2021, v. , p. 103-116.
• Baroni, Rafael ; PREMEBIDA, STHEFANIE ; MARTINS, MARCELLA ; OLIVA, DIEGO ; Freitas de Morais, Erikson ; Santos, Max . Traffic Control Using Image Processing and Deep Learning Techniques. Studies in Computational Intelligence. 1ed.: Springer International Publishing, 2021, v. , p. 319-335.
• Durasevic, Marko ; JAKOBOVIC, DOMAGOJ ; Scoczynski Ribeiro Martins, Marcella ; PICEK, STJEPAN ; WAGNER, MARKUS . Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations. Lecture Notes in Computer Science. 1ed.: Springer International Publishing, 2020, v. , p. 111-124.
• CAMARGO, THIAGO O. ; Premebida, Sthefanie Monica ; PECHEBOVICZ, DENISE ; SOARES, VINICIOS R. ; MARTINS, MARCELLA ; BARONCINI, VIRGINIA ; SIQUEIRA, HUGO ; OLIVA, DIEGO . Solar Spots Classification Using Pre-processing and Deep Learning Image Techniques. Communications in Computer and Information Science. -ed.: Springer International Publishing, 2019, v. , p. 235-246.