Francisco Javier Márquez González is a PhD candidate whose research lies at the intersection of decentralized systems and artificial intelligence. He studies how foundation models can power multi-agent systems that coordinate, reason, and make decisions without relying on a central authority. His current work looks at blockchain-based decentralized systems, with the aim of building trustworthy, transparent, and resilient infrastructures for distributed intelligence.

He holds an M.Sc. in Artificial Intelligence from the Polytechnic University of Madrid, where his master’s thesis explored Estimation of Distribution Algorithms for visualization problems in statistics. He also holds a double bachelor’s degree in Mathematics and Computer Science from the University of Seville, where his bachelor’s thesis studied the NTRU protocol and lattice-based post-quantum cryptography. He also completed an Erasmus+ exchange at Eindhoven University of Technology. This training in cryptography, optimization, and probabilistic modelling gives him a rigorous mathematical base for research on secure decentralized systems.

Alongside his research, he brings industry experience in deploying AI at scale. At Enel (Endesa), he has worked on transformer-based time-series foundation models for electricity demand forecasting. Earlier, at Telefónica, he developed retrieval-augmented generation systems and fraud detection pipelines. Through his work, he aims to advance AI systems that are distributed, interpretable, and reliable.