Summary
Alejandro Marrero is a PhD-trained AI researcher and university lecturer with 11 years of experience designing and deploying machine learning and evolutionary computation systems, currently serving as Profesor Universitario Contratado Interino at Universidad de La Laguna. His research specializes in Quality Diversity (QD), marrying evolutionary algorithms and optimization to produce diverse, robust solutions for combinatorial domains, while his engineering work spans ML/DL, LLM fine-tuning, FastAPI deployments, and HPC-aware C++ implementations. He has a proven track record of moving research into production—building RAG systems, autoencoder solutions for knapsack problems, and cloud-deployed APIs using Docker and AWS. Alejandro combines strong data engineering skills (Pandas, Polars, Dask) with reproducible CI/CD practices, and has supervised multiple undergraduate theses and published at international AI and evolutionary computation venues. Based in Tenerife, he blends academic rigor with practical software craftsmanship and a curiosity for how diverse intelligent systems can tackle real-world optimization challenges.
11 years of coding experience
1 year of employment as a software developer
Bachillerato Bachillerato de Ciencias y Tecnología, Bachillerato Bachillerato de Ciencias y Tecnología at IES Manuel Gonzalez Pérez
PhD in Computer Science Artificial Intelligence Computer Science, PhD in Computer Science Artificial Intelligence Computer Science at Universidad de La Laguna
Spanish, English