I am Matias R. Vazquez, Senior Data Scientist at PhysicsX, where we have a ton of fun building AI systems for advanced engineering applications. I believe that the combination of scientific rigour, creativity and agile ways of working can deeply transform and accelerate the way we design an operate our most complex systems.

Currently my work focuses on the use of Graph Neural Networks (GNNs) and other Deep Learning architectures to model physical systems, with direct applications to the design and operation of advanced engineering projects.

I am interested in all aspects of Machine Learning (ML) - from the abstract mathematical ideas to the MLOps practices that turn them into products and tangible deliverables. I have a track record of ML projects in various industries - some of my favorites have been: mathematical optimisation for Operations Research, Monte Carlo simulations for logistics, and the use of Graph Neural Networks for modelling physical systems

I am (and always will be) a physicist. Before entering the AI industry, I did academic research in particle physics at the University of Paris-Saclay, where I obtained my PhD. I studied the phenomenology of Higgs Bosons at CERN’s particle collider @ Geneva. I am also interested in quantum computing and information. You can find a list of my scientific publications in Google Scholar.

In my free time I enjoy reading, surfing, traveling and trying new sports.