Ruben Morante González

• • Design and implementation of advanced optimization algorithms for routing and logistics use cases.

• • Development of parallel metaheuristic strategies in Java, reducing execution time by up to ~30% compared to baseline implementations.

• • Validation of optimization models using real-world datasets in collaboration with applied research and industrial partners.

• • Technical supervision and mentoring of junior researchers and students, ensuring code quality and reproducibility. Technologies: Java, Parallel Computing, Metaheuristics

• • Designed and implemented production-grade optimization engines for large-scale routing and operational planning problems.

• • Integrated metaheuristic algorithms into Java and Python systems used in real industrial scenarios.

• • Improved solution quality by ~10–20% through algorithmic refinement and hybrid metaheuristic strategies.

• • Reduced computation times by ~25–35% via parallelization and performance-oriented design.

• • Translated business and operational constraints into formal optimization models in close collaboration with cross-functional teams.

• • Maintained CI/CD pipelines and enforced code quality standards in cloud-based environments. Technologies: Java, Python, Spring, Maven, SQL, C++, Azure DevOps, Parallelism

• • Teaching optimization, algorithms, and software engineering subjects at undergraduate and master's level.

• • Supervision of applied optimization and programming projects with real-world constraints.

• • Strengthened leadership and communication skills through technical instruction and mentoring.