Juan Fernández Del Pozo

Juan Fernández del Pozo Romero is a PhD student in Artificial Intelligence at Universidad Politécnica de Madrid, currently working with the Computational Intelligence Group (CIG). His research focuses on interpretable structure learning of Bayesian Networks, particularly in the context of explainable AI (XAI) and its applications in machine learning and optimization.

He previously worked as a Research Assistant on interpretable Bayesian Networks and their industrial applications, collaborating with ArcelorMittal on condition monitoring using probabilistic models. He also gained industry experience as a Junior Consultant at T4S Advance Solutions.

He holds an MSc by Research in AI from Universidad Politécnica de Madrid, where he achieved a perfect thesis grade (10/10) and an overall final grade of 9.16. His academic journey began with a BEng in Computer Science from Universidad Autónoma de Madrid, where he graduated with honors (BEng Thesis: 9.9 MH).

With a strong mathematical foundation and a passion for real-world applications, his expertise lies at the intersection of Bayesian networks, explainable AI, and industrial AI solutions.