Camilo Velázquez-Rodríguez

Camilo Velázquez-Rodríguez

Research Engineer

Flanders Make

Biography

Dr. Camilo Velázquez-Rodríguez is a Research Engineer at Flanders Make, the strategic research centre for the manufacturing industry in Flanders. He works in Digital Productions, part of the ProductionS Core Lab in Kortrijk, Belgium. His focus is on bridging advanced research and the factory floor: he takes industrial data, AI and digital-twin technologies from an idea to a working, deployed solution.

In collaborative projects with industrial partners, he leads the technical work from requirements and architecture through implementation, deployment and testing. Some of the results include:

  • Digital twins of production assets based on industry standards, supporting interoperable data exchange.
  • AI-driven automation that reduces manual, time-consuming engineering tasks.
  • AI-assisted tools for visual inspection and quality control.
  • Data pipelines and cloud-based services that run reliably on real production data.

His background is in software engineering and machine learning. He holds a Ph.D. in Computer Science from the Vrije Universiteit Brussel (VUB), obtained in 2024 under the supervision of Prof. Dr. Coen De Roover, followed by a postdoctoral position at VUB’s Software Languages Lab. His research has received two Distinguished Paper Awards (SANER 2022 and SCAM 2025). Earlier work in optimisation and mathematical modelling gives him a solid quantitative foundation.

Colleagues know him as someone who takes ownership, adapts quickly to new domains and technologies, and communicates clearly with engineers, researchers and decision-makers. He also contributes to Belgian and European research proposals, and he enjoys turning complex requirements into practical solutions with measurable impact.

Interests
  • Industrial AI & Machine Learning
  • Digital Twins & Asset Administration Shell
  • Data Engineering & Analytics
  • Cloud & Edge Software Deployment
  • Software Engineering
Education
  • 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

(2026). Accelerating the Adoption of Asset Administration Shells through AI Agents. In INTELLI 2026.

(2025). Smelling Secrets: Leveraging Machine Learning and Language Models for Sensitive Parameter Detection in Ansible Security Analysis. In SCAM 2025.

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(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). 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:

SCAM 2025 Distinguished Paper Award to: Smelling Secrets: Leveraging Machine Learning and Language Models for Sensitive Parameter Detection in Ansible Security Analysis
SANER 2022 Distinguished Paper Award to: Uncovering Library Features from API Usage on Stack Overflow