Biography:
MCP holds a PhD in Physics from Universidad Complutense de Madrid. He is a member of the Institute for Research in Technology (IIT) and the Interdisciplinary Group of Complex Systems (GISC). MCP has been the Principal Investigator (PI) of six Spanish national research projects and participated in five European projects under Marie Sklodowska-Curie Actions and H2020. The central theme of these projects was the application of Complexity theory to model and predict experimental data in Physics, Biology, and Social Sciences. MCP has published his research in prestigious journals such as PNAS, Nature Communications, Physical Review Letters, and Science Translational Medicine. In this sense, most of the research carried out by the MCP has been carried out in collaboration with experimental groups from all over the world, from Immunology to Condensed Matter. MCP has been a visiting researcher at the Los Alamos National Laboratory (LANL) and a visiting Professor at the University of Leeds (2016-2017)
Areas of interest:
Statistical Mechanics, Nonlinear Physics, Theoretical Immunology, Bayesian Statistics and Epidemiology, Forest fires.
Experience:
He has published in journals such as PNAS, Physical Review Letters, Nature Communications, Science Translational Medicine, Physical Review B, Scientific Reports and Frontiers in Immunology, to name a few. He has been the Principal Investigator of 5 Spanish Ministry of Science research projects. He has participated in 10 projects, including 3 European projects within Marie Sklodowska-Curie Actions (of which he has been the IP of the Comillas node) and H2020. The central theme of these projects was the application of Statistical Mechanics methods to model complex systems, with particular emphasis on modelling and predicting experimental data. Since 2009, all MCP projects have focused on biophysics and theoretical immunology, with around 100 publications in peer-reviewed journals with about 3000 citations. MCP's research has been reviewed in various media (BBC Radio 4, RNE-Radio 1, El País, Muy Interesante, and other Spanish newspapers).
Skills:
MCP's analytical skills include agent-based simulations, stochastic equations, reaction-diffusion equations with a strong emphasis on perturbation and numerical methods. MCP is also an experienced programmer in different programming paradigms (i) General-purpose languages: Python, C, C++, Java; (ii) Scripting languages: Matlab, bash, awk; (iii) Statistical and Bayesian languages: R, JAGS, BUGS; and (iv) Symbolic software: Mathematica, Maple. Recently, MCP has used different Artificial Intelligence tools such as: Bayesian networks, Hidden Markov models, Unsupervised machine learning: clustering or Large language models.
Current research interests:
Complex Systems; Epidemic models; Probabilistic Machine Learning; Theoretical Immunology; Biophysics; Stochastic Processes; Serious Games.