Rubén Infantes
Assistant Professor at Universidad de Málaga
Spain
Summary
👤
Senior🎓
Top SchoolRubén Infantes is an Assistant Professor and researcher specializing in search-based software engineering, multiobjective optimization, and green computing, with a Ph.D. from École Polytechnique de Montréal whose thesis was nominated for a best-thesis award. He combines academic leadership—organizing and serving on committees for ICSE-affiliated workshops and GECCO—with hands-on contributions to prominent open-source tooling like the jMetal framework, where he refactored core multiobjective algorithms. His work bridges theory and practice, applying metaheuristics and machine learning to real-world problems in IoT, sustainability, and software energy efficiency. A recipient of competitive fellowships (Juan de la Cierva, PAIDI) and a track record of publications in top venues (EMSE, IEEE TSE, Evolutionary Computation), he is known for turning complex optimization challenges into usable frameworks and reproducible research.
8 years of coding experience
10 years of employment as a software developer
Bachelor's degree, Computer Engineering, Bachelor's degree, Computer Engineering at Universidad de MálagaDoctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at École Polytechnique de Montréal
Spanish, English, French
Github Skills (7)
javas10
metaheuristics10
java10
data-structure9
algorithm9
data-structures9
algorithms9
Programming languages (3)
Github contributions (5)
jMetal/jMetal
Mar 2018 - Mar 2018
jMetal: a framework for multi-objective optimization with metaheuristics
Role in this project:
Back-end Developer
Back-end DeveloperContributions:8 commits, 4 PRs, 2 comments in 15 days
Contributions summary:Rubén primarily focused on enhancing the `jMetal` framework for multi-objective optimization. Their contributions involved refactoring and modifying core components, such as `GWASFGA`, `WASFGA`, and `GWASFGARanking`, to improve their functionality and address constraint handling. They also made changes to weight vector implementations, including the addition of functionalities for reading and validating them. Overall, the work indicates a focus on algorithm refinement and internal framework improvements.
metaheuristicsmulti-objective-optimizationmultiobjective-optimizationsoftware-frameworkjava
rsain/SoftwareCognitiveComplexityReducer
Jan 2022 - Feb 2026
Contributions:9 pushes, 1 branch in 4 years 2 months
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