José Ramón Dorronsoro is a Doctor (Ph.D.) in Mathematics from Washington University in St Louis, USA, and a Doctor in Mathematical Sciences from the Complutense University of Madrid. He is currently Professor of Computer Science at the Escuela Politécnica Superior (EPS) of the UAM. Professor Dorronsoro has extensive teaching experience in undergraduate and graduate courses. His research covers both theoretical and innovation aspects. The theoretical work has recently focused on: optimization, particularly on the confluence of convex optimization (support vector machines, proximal methods, Nesterov acceleration) with Sparse problems such as Lasso, Total Variation and its group variants, learning deep networks, multitask learning or building SVMs; and  manifold learning, an alternative to the sparse models where it is sought to identify a structure of low dimension in data of a sample of much larger dimension. His innovation work has focused in recent years on smart energy issues, particularly related to the prediction of renewable wind and solar energy. This work has resulted in more than 140 international publications in mathematical analysis, neural networks, machine learning and data science.


  • • A. Torres, C. Alaíz, J.R. Dorronsoro. Faster SVM Training via Conjugate SMO. Pattern Recognition. Volume 111, March 2021.
  • • C. Ruiz, C. Alaíz, J.R. Dorronsoro. Multitask Support Vector Regression for Solar and Wind Energy Prediction. Energies 2020.
  • • Á. Fernández-Pascual, N. Rabin, D. Fishelov, J.R. Dorronsoro. Auto-adaptive multi-scale Laplacian Pyramids for modeling non-uniform data. Engineering Applications of Artificial Intelligence, 2020.
  • • Díaz-Vico, J. Prada, A. Omari, J. R. Dorronsoro. Deep support vector neural networks. Integrated Computer Aided Engeering, 2020.
  • • A. Catalina, C. Alaíz, J. R. Dorronsoro. Combining Numerical Weather Predictions and Satellite Data for PV Energy Nowcasting. IEEE Transactions on Sustainable Energy, 2020.
  • • D. Díaz-Vico, J. R. Dorronsoro. Deep Least Squares Fisher Discriminant Analysis. IEEE Transactions on Neural Networks and Learning Systems, Aug. 2020.
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