Current PhD Students

Current
Imanol Echeverria
Deep learning for real-time scheduling
πŸ› Tecnalia
πŸ‘₯ Co-supervised with Maialen Murua
Current
Alexander Olza
Machine learning methods for brain decoding
πŸ‘₯ Co-supervised with David Soto
Current
IΓ±igo Diez
Machine learning methods for analyzing the Language Connectome
πŸ› BioGuipuzkoa Center
πŸ‘₯ Co-supervised with Ileana Quinones and Usue Mori
Current
Josu Iturralde
Bayesian Physics Informed Neural Networks
πŸ‘₯ Co-supervised with Joxe Aizpurua
Current
Seyma Takir
Manifold-learning methods in brain fMRI data analysis
πŸ‘₯ Co-supervised with David Soto
Current
Machine learning methods for computational modeling of fluid dynamic problems
πŸ‘₯ Co-supervised with Marco Ellero

Former PhD Students

Former
Adversarial examples in the audio domain; adversarial attacks in explainable ML
πŸ‘₯ Co-supervised with Jose Antonio Lozano
Former
Multi-label hierarchical classification methods for NLP
πŸ‘₯ Co-supervised with Jose Antonio Lozano
Former
Investigation of the properties of unconscious visual information processing in the human brain
πŸ‘₯ Co-supervised with David Soto
Former
Artificial intelligence methods for smart electricity grids and energy distribution
Former
Thesis: Vines copulas for machine learning
πŸ‘₯ Co-supervised with Jose Antonio Lozano
Former
Thesis: Neural architecture search of generative and multitask models
πŸ‘₯ Co-supervised with Alexander Mendiburu
Former
Thesis: Mathematical programming and machine learning techniques for problems defined on graphs
πŸ› Tecnalia
πŸ‘₯ Co-supervised with Diego Galar
Former
πŸ‘₯ Co-supervised with A. Mendiburu and J. A. Lozano
Interested in PhD supervision? If you are interested in pursuing a PhD in machine learning, evolutionary computation, or related areas, please contact me with a description of your research interests and a CV.