Marcos Vinícius

ADHEMAR DE BARROS AVENUE · Ondina · Salvador · BA · 40170110 · marcosvsf@ufba.br

Ph.D. student in computer science at Federal University of Bahia (of portuguese, Universidade Federal da Bahia (UFBA)), in Brazil. I received in 2020, my M.Sc. degree in computer science at the UFBA. Graduated in Bachelor of Information Systems from the Federal University of Piauí in 2017. He has experience in Computer Science, with emphasis on Image Processing, Time Series, Machine Learning and Deep Learning, Computer Aided Detection Systems and Fuzzy Logic. With a solid academic background, Marcos has stood out for his innovative research, reflected in publications in high-impact journals and conferences in the field of computer science. Additionally, his collaborative experience with industry, accumulated over more than 4 years, has been a valuable source of learning and practical application.

Education

Federal university of Bahia

Postgraduate Program in Computer Science

Ph.D. student in the area of Artificial Intelligence

2020.2 - Current

Federal university of Bahia

Postgraduate Program in Computer Science

Master in the area of Artificial Intelligence

April 2018.1 - June 2020.1

FEDERAL UNIVERSITY OF PIAUI

Graduate in Information Systems
Automatic methodology for diagnosis of glaucoma using the Deep Learning approach

IRA: 8.0507

February 2014.1 - December 2017.2

Experience

Data Science

Estimating Origin and Destination in Public Transportation
  • Worked on training machine learning models for preprocessing and filtering of images.
  • Worked on developing an ensemble model for facial detection. The ensemble model created is more robust and accurate in detecting faces under different adverse conditions, as it is applied in a real environment, on photos captured inside buses, with varying lighting conditions, pose, occlusion, etc.
  • Worked on developing and fine-tuning models for facial recognition task.
  • Analyzed the racial bias present in some facial detection models, aiming to ensure that the implemented ensemble model is unbiased and addresses ethical concerns.
  • Worked on creating an API for deploying the developed models.
  • Conducted state-of-the-art research and published articles related to the developed application.
2019 - 2021

Machine Learning Engineer

Fraud detection in public transportation
  • Data Analysis and Modeling of Different Public Transportation Databases.
  • Development of a data mining software that estimates boarding and alighting information of passengers in public transportation. The software, given the boarding and alighting information, calculates several indices to assist in the planning and management of public transportation.
  • Validation, analysis, and reporting of processed data.
  • Literature review and writing scientific articles on the obtained results.
2022 - Current

VOLUNTARY SCIENTIFIC INITIATION

Segmentation of Glaucomatous Images Using Deep Learning-Based Approaches

Glaucoma is a complex multifactorial disease, with specific characteristics, in which damage occurs in the optic nerve and progressive and irreversible loss of the visual field. According to the World Health Organization there are around 60 million Glaucomatous diseases worldwide, with more than 2.4 million cases occurring each year. There is still no cure for Glaucoma, but early detection and preventive treatments are the only ways to prevent total loss of vision in affected patients. Thus, this project aims to create a new method of automatic segmentation of Glaucoma using Deep Learning approaches based on the analysis of digital images of the fundus of the eye.

October 2016 - July 2017

Extension Project

Web and mobile application for the dissemination of information from the various sectors and segments of the Senator Campus Helvídio Nunes of Barros.

The project proposed the implementation and implementation of an application on the web and mobile platforms for the dissemination of information from the various sectors and segments of the UFPI - Senador Helvídio Nunes de Barros campus, so that content production and related discussions are decentralized and accessible.

November 2016 - December 2017

JUNIOR DEVELOPER IOS

VILA

Application that presents the city of Oeiras-PI to tourists in a clear and simple way, taking into account not only physical factors but also expose their cultural elements.

November 2015 - November 2016

Skills

Programming Languages & Tools
Building
  • Data Analysis
  • Data Mining
  • Neural Networks, Deep and Shallow using: Pytorch, Tensorflow and Keras
  • Object Detection Models
  • Face Recognition
  • Segmentation and / or clustering of data
  • Data Visualization (matplotlib, seaborn, plotly, ggplot)

Interests

In addition to being a researcher in the area of Artificial Intelligence (AI) reading a lot, I also like to practice challenges in the field, as in Kaggle competitions that help a lot to set learning in AI. On holidays, getting out of the routine, I practice activities such as fishing, swimming, soccer, sports, and cycling.

When indoors, I watch science fiction, fantasy and documentary films. I am an aspiring chef, and I spend a great deal of my free time exploring the latest technological advancements in the world of Machine Learning primarily.

Publications & Certifications

  • FERREIRA, M. V. S.; LOPES, T. J. S. ; RIOS, R. A. ; RIOS, TATIANE N. Modeling Protein Activities and Mutations with Graph Neural Networks: Insights into Hemophilia. In: IEEE International Joint Conference on Neural Networks, 2023, Gold Coast. IEEE International Joint Conference on Neural Networks (IJCNN 2023), 2023.
  • FERREIRA, MARCOS V.; NOGUEIRA, TATIANE ; RIOS, RICARDO A. ; LOPES, TIAGO J. S. C. A graph-based machine learning framework identifies critical properties of FVIII that lead to hemophilia A. Frontiers in Bioinformatics, v. 3, p. 34, 2023.
  • FERREIRA-MARTINS, ANDRÉ J. ; CASTALDONI, RODRIGO ; ALENCAR, BRENNO M. ; FERREIRA, MARCOS V. ; NOGUEIRA, TATIANE ; RIOS, RICARDO A. ; LOPES, TIAGO J. S. . Full-scale network analysis reveals properties of the FV protein structure organization. Scientific Reports, v. 13, p. 1, 2023.
  • Tiago J S Lopes, Ricardo A Rios, Tatiane N Rios, Brenno M Alencar, Marcos V Ferreira, Eriko Morishita. Computational analyses reveal fundamental properties of the AT structure related to thrombosis. Bioinformatics Advances, Volume 3, Issue 1, 2023, vbac098.
  • CANÁRIO, JOÃO PAULO ; FERREIRA, MARCOS VINÍCIUS ; FREIRE, JUNOT ; CARVALHO, MATHEUS ; RIOS, RICARDO. A face detection ensemble to monitor the adoption of face masks inside the public transportation during the COVID-19 pandemic. Multimedia Tools and Applications, 2022.
  • FERREIRA, MARCOS VINÍCIUS DOS SANTOS; RIOS, RICARDO; RIOS, TATIANE NOGUEIRA. sci-FTS: Using soft clustering on Intrinsic Mode Functions to model Fuzzy Time Series. Software Impacts, v. 11, p. 100230, 2022.
  • FERREIRA, MARCOS VINÍCIUS DOS SANTOS; RIOS, RICARDO; MELLO, RODRIGO; RIOS, TATIANE NOGUEIRA. Using fuzzy clustering to address imprecision and uncertainty present in deterministic components of time series. APPLIED SOFT COMPUTING, v. 113, p. 108011, 2021.
  • FERREIRA, M. V. S.; ALMEIDA, A. ; CANARIO, J. P. ; SOUZA, M. ; NOGUEIRA, T. ; RIOS, R. A. Ethics of AI: Do the face detection models act with prejudice?. In: Brazilian Conference on Intelligent Systems (BRACIS), 2021, São Paulo. Proceedings of the 9th Brazilian Conference on Intelligent Systems (BRACIS), 2021.
  • FERREIRA, MARCOS VINÍCIUS DOS SANTOS; FILHO, A. O. DE C.; DALÍLIA DE SOUSA, A.; C. S., ARISTÓFANES; G., MARCELO. Convolutional neural network and texture descriptor-based automatic detection and diagnosis of glaucoma. EXPERT SYSTEMS WITH APPLICATIONS, v. 110, p. 250-263, 2018.
  • FERREIRA, M. V. S.; CARVALHO, E. D.; SOUSA, A. D.; CARVALHO FILHO, A. O.. Processamento Digital de Imagens Médicas com Python e OpenCV. In: Ricardo de Andrade L. Rabêlo, Thiago C. de Sousa e Rodrigo Augusto R. S. Baluz.. (Org.). Anais Eletrônicos ENUCOMP 2017. 1ed. PARNAÍBA: Fundação Universidade Estadual do Piauí-FUESPI, 2017, v. , p. 678-701.
  • FERREIRA, M. V. S.; OLIVEIRA, K. M. S. ; CARVALHO FILHO, A. O. ; SOUSA, A. D.. Deep Learning: Uma Introdução às Redes Neurais Convolucionais. In: Ricardo de Andrade L. Rabêlo, Thiago C. de Sousa e Rodrigo Augusto R. S. Baluz.. (Org.). Anais Eletrônicos ENUCOMP 2017. 1ed. PARNAÍBA: Fundação Universidade Estadual do Piauí-FUESPI, 2017, v. , p. 786-806.
  • FERREIRA, M. V. S.; SOUSA, A. D.; CARVALHO FILHO, A. O.; DRUMOND, P. M. L. L.; BARROS, P. V. S.. Metodologia automática para diagnóstico do glaucoma usando abordagem Deep Learning. In: Encontro Nacional de Inteligência Artificial e Computacional, 2017, Uberlândia. ENIAC. Uberlândia: SBC, 2017. v. XIV. p. 936-947..
  • CARVALHO, E. D.; FERREIRA, M. V. S.; LEAL, R.; SILVA, F. A.. Análise de Desempenho de um Sistema Distribuído para Segmentação de Imagens da Retina. In: Encontro Unificado de Computação - ENUCOMP, 2017, Parnaíba. Anais Eletrônicos ENUCOMP 2017. PARNAÍBA: Fundação Universidade Estadual do Piauí-FUESPI, 2017. v. 10. p. 196-203.
  • FERREIRA, M. V. S.; SOUSA, A. D. ; CARVALHO FILHO, A. O. ; BARROS, P. V. S. ; DRUMOND, P. M. L. L. . Diagnóstico Automático do Glaucoma usando Convolutional Neural Network e Descritores de Textura. In: Encontro Unificado de Computação - ENUCOMP, 2017, PARNAÍBA. Anais Eletrônicos ENUCOMP 2017. PARNAÍBA: Fundação Universidade Estadual do Piauí-FUESPI, 2017. v. 1. p. 220-227.