Robert Planas is a data scientist and SEM analyst based in Barcelona with 11 years of multidisciplinary experience spanning biomedical, aerospace, and mathematical engineering. He holds dual MSc degrees in Mechanical & Aerospace Engineering (UCI) and Biomedical Engineering (VIU) and dual BSc training in Mathematics and Aerospace from CFIS-UPC, blending rigorous theory with applied research. At Gauss & Neumann he applies ML and statistical techniques to real-world problems while his research background includes transferable deep learning for PDEs, physics-informed neural networks, and evolutionary Gaussian processes with three first-author publications from UCI’s PMACS lab. His biomedical internships at Sant Joan de Déu and IRI focused on explainable AI for rare disease diagnosis and confocal microscopy image analysis, highlighting a track record of deploying ML toward trusted clinical decision-making. Not obvious from the title: he bridges control/dynamical-systems thinking from his UCSD and control-focused undergraduate work into probabilistic and evolutionary approaches for extrapolation and interpretability. This combination makes him adept at taking principled research methods into production-facing analytics and diagnostic applications.
11 years of coding experience
2 years of employment as a software developer
University of California, Irvine
University of California, San Diego
UPC Universitat Politècnica de Catalunya
Master of Science - MS, Biomedical/Medical Engineering, Master of Science - MS, Biomedical/Medical Engineering at VIU - Universidad Internacional de Valencia
Bachelor's degree, Mathematics and Aerospace Engineering, Bachelor's degree, Mathematics and Aerospace Engineering at CFIS-UPC
International Baccalaureate, International Baccalaureate at International Baccalaureate
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