Rafael Ballester-Ripoll

Since 2019, Rafael Ballester-Ripoll is an Assistant Professor at the IE University in the area of data science and machine learning. Prior to that, he was a Postdoctoral Associate at the Swiss Federal Institute of Technology in Zurich (ETH) and at the University of Zurich (UZH). He holds a PhD in Computer Science from UZH (2017) as well as BSc and MSc degrees in Mathematics and Computer Science from the Technical University of Catalonia-UPC (2012).

His research interests lie in data analysis, explainable artificial intelligence, and sensitivity analysis using modeling tools such as low-rank decompositions, tensor networks, and neural networks. His contributions in large-scale scientific visualization, data compression, and uncertainty quantification using these tools have been published in the Journal of Machine Learning Research, Journal of Reliability Engineering and System Safety, IEEE Transactions in Visualization and Computer Graphics, and the SIAM/ASA Journal on Uncertainty Quantification, among other journals. He also partakes regularly in academic conferences including IEEE VIS, EuroVis, meetings of the Society for Industrial and Applied Mathematics, and various symposia on tensor methods.

ACADEMIC EXPERIENCE

• Assistant Professor at IE University, 2019 – Present

• Postdoc at the CSE-LAB group, ETH Zurich, 2019 – 2019

• Postdoc at the VMML lab, University of Zurich, 2017 – 2019

• Doctoral student at the VMML lab, University of Zurich, 2012 – 2017

ACADEMIC BACKGROUND

• PhD in Computer Science (University of Zurich), Zurich, Switzerland, 2017

• BSc and MSc in Computer Science, (Technical University of Catalonia-UPC), Barcelona, Spain, 2012

• BSc and MSc in Mathematics, (Technical University of Catalonia-UPC), Barcelona, Spain, 2012

SELECTED PUBLICATIONS

• M. Usvyatsov, R. Ballester-Ripoll, K. Schindler (2022). “tntorch: Tensor Network Learning with PyTorch”, Journal of Machine Learning Research, Vol. 23 (208): 1-6.

• R. Ballester-Ripoll, M. Leonelli (2022). “Computing Sobol Indices in Probabilistic Graphical Models”, Reliability Engineering and System Safety, Vol. 225: 108573.

• R. Ballester-Ripoll (2021). “Tensor Approximation of Cooperative Games and Their Semivalues”, International Journal of Approximate Reasoning, Vol. 142: 94-108.

• Ballester-Ripoll, R., Lindstrom, P., Pajarola, R. (2020). “TTHRESH: Tensor Compression for Multidimensional Visual Data”. IEEE Transactions on Visualization and Computer Graphics, Vol. 26 (9): 2891-2903

• Ballester-Ripoll, R., Paredes, E.G., Pajarola, R. (2019). “Sobol Tensor Trains for Global Sensitivity Analysis”. Reliability Engineering & System Safety, Vol. 183: 311-322