Machine Learning Researcher at Lawrence Livermore National Laboratory (Computational Engineering Directorate), holding a Ph.D. from Université Pierre et Marie Curie and Inria. Awarded with the SMAI-GAMNI award 2017 (French Society of Industrial and Applied Mathematics) for the best thesis in numerical methods for the mechanical and engineering sciences. Skilled in Scientific Computing, Machine Learning, Computational Mechanics and Mathematical Modeling. Educated at University of the Basque Country and Utrecht University. Author name in papers is Mikel Landajuela.

Webpage: https://landajuela.github.io/

Google Scholar : https://scholar.google.com/citations?user=Tl93fucAAAAJ&hl=en

Ph.D. Computational and Applied Mathematics, Université Pierre et Marie Curie and Inria, Paris, France

B.S. and M.S Mathematical Sciences, University of the Basque Country, Bilbao, Spain

Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding,Curran Associates, Inc.,34,Advances in Neural Information Processing Systems,2021,24912--24923,Mundhenk, Terrell and Landajuela, Mikel and Glatt, Ruben and Santiago, Claudio P and faissol, Daniel and Petersen, Brenden K

Discovering symbolic policies with deep reinforcement learning,PMLR,139,Proceedings of the 38th International Conference on Machine Learning,2021,5979--5989,Landajuela, Mikel and Petersen, Brenden K and Kim, Sookyung and Santiago, Claudio P and Glatt, Ruben and Mundhenk, Nathan and Pettit, Jacob F and Faissol, Daniel

Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients,OpenReview.net,9th International Conference on Learning Representations, {ICLR} 2021, Virtual Event, Austria, May 3-7, 2021,2021,Brenden K. Petersen and Mikel Landajuela and T. Nathan Mundhenk and Claudio Prata Santiago and Sookyung Kim and Joanne Taery Kim

Splitting schemes and unfitted-mesh methods for the coupling of an incompressible fluid with a thin-walled structure,IMA Journal of Numerical Analysis,40,2019,1407-1453,Fernandez, Miguel A and Landajuela, Mikel

Numerical approximation of the electromechanical coupling in the left ventricle with inclusion of the Purkinje network,International Journal for Numerical Methods in Biomedical Engineering,34,2018,e2984,Landajuela, Mikel and Vergara, Christian and Gerbi, Antonello and Ded{\`e}, Luca and Formaggia, Luca and Quarteroni, Alfio

Mathematical and Numerical Description of the Heart Function,Springer International Publishing,Imagine Math 6: Between Culture and Mathematics,2018,171--177,Quarteroni, Alfio and Vergara, Christian and Landajuela, Mikel

Coupling schemes for the FSI forward prediction challenge: Comparative study and validation,International Journal for Numerical Methods in Biomedical Engineering,33,2017,e2813,Landajuela, Mikel and Vidrascu, Marina and Chapelle, Dominique and Fernandez, Miguel A.

Robin-Neumann Schemes for Incompressible Fluid-Structure Interaction,Springer International Publishing,Domain Decomposition Methods in Science and Engineering XXII,2016,65--76,Fernandez, Miguel A. and Landajuela, Mikel and Mullaert, Jimmy and Vidrascu, Marina

Nitsche-XFEM for the coupling of an incompressible fluid with immersed thin-walled structures,Computer Methods in Applied Mechanics and Engineering,301,2016,300-335,Frederic Alauzet and Benoit Fabr{\`e}ges and Miguel A. Fernandez and Mikel Landajuela

Coupling schemes and unfitted mesh methods for fluid-structure interaction,PhD Thesis, 2016,Landajuela, Mikel

Fully decoupled time-marching schemes for incompressible fluid/thin-walled structure interaction,Journal of Computational Physics,297,2015,156-181,Miguel A. Fernandez and Mikel Landajuela and Marina Vidrascu

Splitting schemes for incompressible fluid/thin-walled structure interaction with unfitted meshes,Comptes Rendus Mathematique,353,2015,647-652,Miguel A. Fernandez and Mikel Landajuela

A fully decoupled scheme for the interaction of a thin-walled structure with an incompressible fluid,Comptes Rendus Mathematique,351,2013,161-164,Miguel Angel Fernandez and Mikel Landajuela

Burgers equation,BCAM Internship report: Basque Center for Applied Mathematics,2011,Landajuela, Mikel

 

• Interpretable Symbolic Regression for Data Science: Real-world track, Wed 13 Jul 2022, https://cavalab.org/srbench/competition-2022/
• ECCOMAS PhD Award, Fri 31 Mar 2017, http://eccomas.cimne.com/vpage/1/6/2016
• SMAI PhD Award, Thu 2 Feb 2017, http://smai.emath.fr/spip.php?article165&lang=fr