MARTIN Research Group @ LNCC
Modeling and analysis of user and system behavior in complex systems

Antônio Tadeu Gomes

Head of the MARTIN Research Group, he is a researcher at the National Laboratory for Scientific Computing (LNCC) since 2005. He is currently the executive officer of the Brazilian National System for High-Performance Computing (SINAPAD), and coordinator of the Steering Committee of the Santos Dumont supercomputing facility (SDumont). He is also the current deputy coordinator of the LNCC's Graduate Program in Computational Modeling (PPG-LNCC). He received his Ph.D. in Computer Science from the Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil, in 2005. His main interests are in the broad area of systems modeling, encompassing networked systems, distributed systems, numerical simulation systems, high-performance computing systems, and machine learning systems. He is a member of the Association for Computing Machinery (ACM) and the Brazilian Computer Society (SBC). He was recipient of the productivity research award PQ-2 from the Brazilian Research Council (CNPq) from 2010 to 2018.

Caroline de Oliveira Costa Souza

She earns a bachelor's degree in Production Engineering from the Fluminense Federal University (2017) and a master's degree in Computational Modeling in Science and Technology from the same university (2019). She received a doctor's degree in Computational Modeling from the National Laboratory for Scientific Computing in 2024. Her main areas of interest are: patient pathways, process mining, complex networks, renewable energy complementarity and interdisciplinary research.

Haron Calegari

He is Bachelor in Production Engineering from Multivix-ES (2014), with experience in Industry and Teaching in higher education. Master in Computational Modeling from LNCC (2017) with emphasis on Complex Networks and Mobility Analysis. Currently, doctorate student at LNCC with emphasis on the use of Physical Principles applied in Machine Learning Models, and also Professor at the Federal Center for Technological Education (CEFET-RJ).

Juan Humberto Leonardo Fabian

He is Bachelor of Scientific Computing from Universidad Nacional Mayor de San Marcos (Lima, Peru - 2013). Master's degree in Computational Modeling at LNCC (2016), studying calibration of tumor growth models. Doctor degree in Computational Modeling at LNCC (2022), working on machine learning applied to resource consumption prediction of multiscale numerical simulations. Currently a post-doc at LNCC working on modeling the behavior of users in SDumont.

Klaus Wehmuth

After a couple of decades in the ICT industry, he came back to academia and now holds a Ph.D. in Computational Modeling at the National Laboratory for Scientific Computing (LNCC). He also holds a B.Sc. degree in Information Systems and a M.Sc. degree in Computational Modeling. His current research interests include applied mathematics, network science, and complex dynamic networks.

Arthur Craveiro

He is a Web Development Technician certified from IFRN (2018) and a Mathematics graduate from UFRN (2023), currently pursuing a Master's degree at LNCC, focusing on user analysis in supercomputing environments using graph-based methodologies.

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João Pedro Macleure Nunes dos Santos

He has a B.Sc. degree in Information Systems from Catolic University of Brasília (UCB) and a M.Sc. degree in Computational Modeling from National Laboratory for Scientific Computing (LNCC). His current research interests includes systems performance analysis, data analysis and computational modeling.

Welber Paraizo

He has a Degree in Mathematics from State University of Montes Claros (UNIMONTES - 2020). MSc candidate in Computational Modeling at the National Scientific Computing Laboratory - LNCC, since 2024.

Alex Borges Vieira

He received the Ph.D. degree in computer science from UFMG, Brazil. He is an Associate Professor with the Computer Science Department, UFJF, Brazil. In 2019, he was a Visiting Professor with LNCC, Brazil. He has productivity in research scholarship, awarded by the Brazilian National Council for Technological and Scientific Development (CNPq). His research interests include network modeling and analysis, and network science.

Jesuliana Ulisses

She is a professor at the Federal University of São João Del Rei. Graduated in Computer Science with a bachelor's degree in Computer Science from the Federal University of Juiz de Fora (UFJF), Master's degree in Computer Science from the Federal Fluminense University (UFF) and PhD in Computational Modeling from UFJF. Post-doctorate at the National Laboratory for Scientific Computing (LNCC) in the area of ​​epidemiological modeling. She worked as a professor in private and public institutions, teaching subjects in the area of ​​computing. She has experience in the area of ​​Computer Science and Computational Modeling, working mainly on the following topics: Digital Image Processing, Computational Modeling in Physiology and Epidemiology, Complex Networks.

Marcia Ito

She is a medical doctor (EPM/UNIFESP), data processing technologist (FATEC-SP), PhD in electrical engineering (EPUSP). Advisor in the master’s Program in Productive Systems at CPS, Professor at FATEC-SP. Fellow of the International Academy of Health Science Informatics and member of the Telehealth Working Group of the International Medical Informatics Association. Also, she is a member of the management committee of the Brazilian Computer Society's Special Commission on Computing Applied to Health. She was General Coordinator of Strategic Information Management at the Ministry of Health (DEMAS/SE/MS) (2019-2020), a researcher at IBM Research Brazil (2012-2018) and editor-in-chief of the Journal of Health Informatics of the Brazilian Society of Health Informatics (2020-2024).

Gladis Cristina Ribeiro

She holds a bachelor's degree in Computer Science and an MBA in Economic and Strategic Project Management (2011) from Fundação Getulio Vargas. Since 2024, she has been pursuing a Master's Degree in Management and Technology in Productive Systems at CPS. With over 30 years of experience, including senior management roles in global corporations like IBM and Kyndryl, she has developed expertise across multiple sectors and is currently specializing in healthcare. Her academic interests include data analysis, process mining, digital transformation, complex networks, and interdisciplinary research in management and technology for productive systems, with a focus on fostering collaboration and bridging theoretical advancements with practical applications.

Other collaborators

Artur Ziviani

Received the Ph.D. degree in computer science from UPMC - Sorbonne Universitès, Paris, France, in 2003. He was a Senior Researcher with National Laboratory for Scientific Computing (LNCC), Brazil. His research interests included network modeling and analysis, network science, and interdisciplinary data science with a networking approach. He was a Member of SBC (the Brazilian Computer Society), an Affiliated Member of the Brazilian Academy of Sciences (2013–2017), and a Senior Member of ACM and IEEE.

Support for Users and Supercomputing Projects in the State of Rio de Janeiro in the Efficient Use of the Santos Dumont Multiuser Computing Environment

The main objective of this project is to create a support service for users and supercomputing projects in the State of Rio de Janeiro. This service will include analysis and optimization activities for both the allocation of SDumont resources and the execution of applications on these resources. To this end, statistical analysis techniques will be employed, aiming at fine-tuning application configuration parameters guided by machine learning, or recoding guided by profiling of the software of these applications.

National Institute of Science and Technology on Scientific Computing-Assisted Medicine (INCT-MACC)

This project aims to promote cutting-edge research and development, focused on scientific computing and its applications in medicine. It focuses especially on some areas, such as: Computer modeling and simulation of the physiological systems that make up the human body; Development of medical image processing through scientific visualization and virtual reality; Developing and managing high-performance computing environments that meet the needs of scientific computing-assisted medicine in the country; Training human resources and promoting the transfer of technology and innovation for the area of healthcare assisted by scientific computing for society as a whole and also for the public and private sectors; Promoting and consolidating, at the national and international levels, the Cooperative and Integrated Network of R&D and FRH in Scientific Computing-Assisted Medicine.