Camilo Velázquez-Rodríguez

Camilo Velázquez-Rodríguez

Postdoctoral Researcher

Vrije Universiteit Brussel

Biography

Camilo Velázquez-Rodríguez is a Postdoctoral researcher at the Software Languages Lab from the Department of Informatics, Faculty of Sciences and Bioengineering Sciences at the Vrije Universiteit Brussel in Brussels, Belgium. His research interests include (but are not limited to) library usages in large software ecosystems, optimisation techniques, machine and deep learning and mathematical modelling. He did his Ph.D. thesis under the supervision of Prof. Dr. Coen De Roover.

Interests
  • Artificial Intelligence
  • Software Engineering
  • Mining Software Repositories
  • Optimisation Techniques
  • Mathematical Modelling
Education
  • Postdoctoral Researcher, 2024-present

    Vrije Universiteit Brussel (VUB)

  • Ph.D. in Computer Science, 2018-2024

    Vrije Universiteit Brussel (VUB)

  • M.Sc. in Applied Mathematics and Informatics for Administration, 2014-2016

    Universidad de Holguín "Oscar Lucero Moya" (UHO)

  • B.Sc. in Informatics, 2009-2014

    Universidad de Holguín "Oscar Lucero Moya" (UHO)

Publications

(2023). A Text Classification Approach to API Type Resolution for Incomplete Code Snippets. In SCICO 2023.

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(2022). LiFUSO: A Tool for Library Feature Unveiling based on Stack Overflow Posts. In ICSME 2022.

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(2022). Uncovering Library Features from API Usage on Stack Overflow. In SANER 2022.

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(2021). On the practice of semantic versioning for Ansible galaxy roles: An empirical study and a change classification model. In JSS 2021.

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(2021). Identifying Versions of Libraries used in Stack Overflow Code Snippets. In MSR 2021.

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(2020). MUTAMA: An Automated Multi-label Tagging Approach for Software Libraries on Maven. In SCAM 2020.

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(2020). Does Infrastructure as Code Adhere to Semantic Versioning? An Analysis of Ansible Role Evolution. In SCAM 2020.

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(2020). Automatic library categorization. In SoHeal 2020.

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(2018). Improving the genetic bee colony optimization algorithm for efficient gene selection in microarray data. In Progress in Artificial Intelligence.

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(2017). Data mining process for identification of non-spontaneous saccadic movements in clinical electrooculography. In Neurocomputing.

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(2017). Automatic Glissade Determination Through a Mathematical Model in Electrooculographic Records. In IWBBIO 2017.

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(2015). Evaluation of Fitting Functions for the Saccade Velocity Profile in Electrooculographic Records. In IWANN 2015.

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(2015). Non Spontaneous Saccadic Movements Identification in Clinical Electrooculography Using Machine Learning. In IWANN 2015.

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(2014). A Comparison of Two Fitting Functions for Sacadic Pulse Component Mathematical Modelling. In ANNIIP 2014.

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Awards

I have been very honoured to receive the following awards:

SANER 2022 Distinguished Paper Award to: Uncovering Library Features from API Usage on Stack Overflow