Allan Pinto

Allan Pinto

Research Leader

CNPEM/LNLS

About Me

I am a Researcher of the Brazilian Synchrotron Light Laboratory (LNLS-Sirius), which is part of the Brazilian Center for Research in Energy and Materials (CNPEM), and responsible for operating the Sirius particle accelerator, Brazil. I received a B.Sc. degree in Computer Science from the University of São Paulo (USP), Brazil, an M.Sc. in Computer Science from the University of Campinas (Unicamp), Brazil, and a Ph.D. degree in Computer Science at the same university. A part of my doctoral was accomplished at the University of Notre Dame, USA. Currently, I am a Research Leader of the Data Science and Management Group at the LNLS-Sirius.

Interests
  • Data Science
  • Artificial Intelligence
  • Machine Learning
  • Computer Vision
  • High-Performance Machine Learning
  • Synchrotron Radiation Applications
  • X-ray Data Analysis
Education

  • PhD in Computer Science, 2018

    University of Campinas (IC/Unicamp)

  • MSc in Computer Science, 2013

    University of Campinas (IC/Unicamp)

  • BSc in Computer Science, 2011

    University of São Paulo (ICMC/USP)

Recent Publications

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Di Wu, Jincheng Liu, Manuel Córdova, Christina Carrozzo Hellevik, Jakob Bonnevie Cyvin, Allan Pinto., Ibrahim A. Hameed, Helio Pedrini, Ricardo da Silva Torres, Annik Magerholm Fet (2023). The PlastOPol system for marine litter monitoring by citizen scientists. Environmental Modelling & Software.

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Pedro I. C. Claro, Egon P. B. S. Borges, Gabriel R. Schleder, Nathaly L. Archilha, Allan Pinto., Murilo Carvalho, Carlos E. Driemeier, Adalberto Fazzio, Rubia F. Gouveia (2023). From micro- to nano- and time-resolved x-ray computed tomography: Bio-based applications, synchrotron capabilities, and data-driven processing. Applied Physics Reviews.

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Maria Cecília Moraes Frade, Thomas Beltrame, Mariana de Oliveira Gois, Allan Pinto., Silvia Cristina Garcia de Moura Tonello, Ricardo da Silva Torres, Aparecida Maria Catai (2023). Toward characterizing cardiovascular fitness using machine learning based on unobtrusive data. PLOS ONE.

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Rodrigo Rico Bini, Gil Serrancoli, Paulo Roberto Pereira Santiago, Allan Pinto., Felipe Moura (2023). Criterion validity of neural networks to assess lower limb motion during cycling. Journal of Sports Sciences.

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Leandro Stival, Allan Pinto., Felipe dos Santos Pinto de Andrade, Paulo Roberto Pereira Santiago, Henrik Biermann, Ricardo da Silva Torres, Ulisses Dias (2023). Using machine learning pipeline to predict entry into the attack zone in football. PLOS ONE.

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Awards

Organized by Europe Spacial Agency (ESA)
Measuring Airport Activity from Sentinel-2 Imagery to Support Decision-Making during the Pandemic
Organized by Coordination of Superior Level Staff Improvement (CAPES)
1st Place Winner of Best Computer Science Ph.D. Thesis (National)
Organized by the Institute of Computing (IC/Unicamp)
Best Computer Science Ph.D. Thesis of the IC/Unicamp in 2018.

Popular Topics

Biometrics Computer Vision Digital Image Forensics Face Recognition Fingerprint Recognition Graph Theory Image Filtering Image Phylogeny Image Provenance Analysis Image Retrieval Information Security Iris Recognition Machine Learning Mobile Devices Multimedia Forensics Presentation Attack Detection Social Networking Synchrotron Radiation Application Text Localization Text Recognition

Contact

  • allan.pinto@lnls.br
  • +55 (19) 3518-2594
  • Rua Giuseppe Máximo Scolfaro, 10.000, Polo II de Alta Tecnologia de Campinas, Campinas, SP 13083-100
  • Data Science and Management Group is located at the LNLS building.