Rafael Ballester-Ripoll

Rafael Ballester-Ripoll is an Assistant Professor at IE University's School of Science & Technology, specializing in Data Science and Machine Learning. Before joining IE in 2019, he held postdoctoral positions at ETH Zurich and the University of Zurich (UZH). He earned his PhD in Computer Science from UZH (2017), and BSc/MSc degrees in Mathematics and Computer Science from the Technical University of Catalonia-UPC (2012).

His research focuses on low-rank tensor decompositions, explainable AI, sensitivity analysis, and scientific visualization. Key contributions include advancements in large-scale visualization, data compression, and uncertainty quantification. Recent work (2025) explores CSR authenticity in AI-era social media, hexagonal A-Star algorithms for weather routing, and entropy coding for tensor networks.

Publications span journals like Journal of Machine Learning Research, IEEE Transactions on Visualization and Computer Graphics, and SIAM/ASA Journal on Uncertainty Quantification. He actively participates in conferences such as IEEE VIS and EuroVis, and co-developed tools like tntorch and VIAN.

His research trends emphasize tensor-based methods applied to interdisciplinary domains, including quantum computing, Bayesian networks, and probabilistic graphical models. Collaborative projects highlight applications in ocean engineering, film analysis, and recommender systems.

Ballester-Ripoll has contributed to IE's Research Datalab initiatives, though no formal awards or grants are explicitly noted in the provided texts. His work bridges theoretical foundations with practical tools for data-driven decision making.