Alejandro Estrada Moreno

Alejandro Estrada Moreno is an Assistant Professor and Tenure-Eligible Lecturer at the Department of Computer Engineering and Mathematics at Universitat Rovira i Virgili (URV), Tarragona, Spain. He leads research in the Research Group on Discrete Mathematics, focusing on Graph Theory, Combinatorics, and Operations Research applications. His academic journey includes a PhD from URV (2016, Summa Cum Laude) under Professors Juan Alberto Rodríguez Velázquez and Ismael González Yero, followed by postdoctoral work at the Open University of Catalonia's ICSO group.

Education:

• Bachelor’s Degree in Computer Science, University of Havana (2006)
• Master’s Degree in Mathematics, University of Havana (2012)
• PhD in Computer Science and Mathematics, URV (2016)

Research Interests: His work bridges theoretical contributions in graph metrics (e.g., metric dimensions, domination theory) with practical applications in logistics optimization, disaster risk modeling, and smart city technologies. Key areas include graph products, secure domination, and simheuristic algorithms for stochastic problems.

Publications & Impact: With 41 peer-reviewed articles (29 JCR-indexed), he contributes to top venues like Theoretical Computer Science and Applied Mathematics and Computation. His applied work addresses real-world challenges in supply chain optimization, earthquake risk insurance, and IoT-driven logistics.

Awards & Roles:

• Martí Franquès Predoctoral Scholarship (2016)
• ANECA accreditation as Associate Professor (2019)
• Reviewer for 25+ journals/conferences
• Principal researcher in 9 projects since 2017

Teaching & Outreach: Full-time faculty at URV since 2014, with part-time roles at Euncet Business School (2018–2019) and Cuba’s Central University (2007–2012). Courses span algorithms, discrete mathematics, and optimization.

Labs & Teams: Active in the Discrete Mathematics Research Group (URV) and the ICSO group (UOC), collaborating on projects like parametric insurance solutions and agri-food supply chain optimization.