Biography:
Simón Rodríguez Santana holds a degree in Physics from the Autonomous University of Madrid, a Master's in Theoretical Physics, and a PhD in Mathematical Engineering, Statistics, and Operations Research from the Complutense University of Madrid. As a researcher, his work focuses on the development of new techniques in probabilistic machine learning and statistics, combining the Bayesian perspective with the usual language of machine learning to solve real-world problems such as drug discovery, adversarial risk analysis, and time series prediction. He has published several high-impact articles in prestigious international journals and conferences, and has also participated in various national and international research projects, serving as principal investigator on two industrial projects. He is currently a professor at the School of Engineering (ICAI) at Comillas Pontifical University, where he is a tenured professor of courses in the degree program "Mathematical Engineering and Artificial Intelligence" and has supervised bachelor's and master's theses. He holds a PAD accreditation from ANECA and has been a visiting scholar at Aalto University (Espoo, Finland).
Areas of interest:
Probabilistic Machine Learning, Bayesian Statistics, Approximate Inference, Operations Research
Experience:
Postdoctoral researcher at the Institute of Mathematical Sciences (ICMAT-CSIC). Member of national and international research projects on applied machine learning research.
Skills:
Programming: Python (including Tensorflow and PyTorch), R. Usage of LaTeX, Git, Slurm Workload Manager, LaTeX, Git, Rmd
Current research interests:
Machine Learning, Probabilistic Machine Learning, Approximate Inference, Bayesian Statistics
F. Estebaranz-Sánchez, K. Kit, J.J. Ibáñez Estevez, D. Ríos Insua, S. Rodríguez-Santana, L.M. Martínez, "Machine learning approaches to dietary classification from dental microtexture in primates", Scientific Reports, Vol. 16, pp. 23378, 2026. [Online: April 2026] doi: 10.1038/s41598-026-47350-8
L. Hidalgo-Trujillo, F. Estebaranz-Sánchez, A.E. Dyowe Roig, I. Bayón Jiménez-Ugarte, X. Albizu-Arias, D. Ríos Insua, J.J. Ibáñez Estevez, A. Pérez-Pérez, J. Pizarroso, B. Ruesca-Bonet, S. Rodríguez-Santana, L.M. Martínez, "Dietary ecology and niche differentiation of Pliocene-Pleistocene papionins from the Turkana Basin inferred from buccal dental microwear texture analysis and machine-learning approaches", Palaeogeography, Palaeoclimatology, Palaeoecology, Vol. 701, pp. 114119, November 2026. [Online: August 2026] doi: 10.1016/j.palaeo.2026.114119
E. González García, P. Varas, P. González-Naranjo, E. Ulzurrun, G. Marcos-Ayuso, C. Pérez, J.A. Páez, D. Ríos Insua, S. Rodríguez-Santana, N.E. Campillo, "AI-Driven De Novo Design and Development of Nontoxic DYRK1A Inhibitors", Journal of Medicinal Chemistry, Vol. 68, nº. 10, pp. 10346 - 10364, May 2025. [Online: May 2025] doi: 10.1021/acs.jmedchem.5c00512
L.A. Ortega, S. Rodríguez-Santana, D. Hernández-Lobato, "Scalable Linearized Laplace Approximation via Surrogate Neural Kernel", presented at 34th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - ESANN 2026, Bruges, Belgium, 22-24 April 2026. In: ESANN 2026: Proceedings 34th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pp. 709-714, doi: 10.14428/esann/2026.ES2026-71
L.A. Ortega, S. Rodríguez-Santana, D. Hernández-Lobato, "Variational Linearized Laplace Approximation for bayesian deep learning", presented at 41st International Conference on Machine Learning - ICML 2024, Vienna, Austria, 21-27 July 2024. In: Proceedings of Machine Learning Research, vol. 235, pp. 38815-38836