I am a machine learning engineer at Epirus in Torrance, California. I am in charge of modeling radio-frequency power amplifiers using neural networks with applications to RF design, RF simulations, digital pre-distortion and other microwave systems.
I was a machine learning researcher at the German Research Center for Artificial Intelligence (DFKI) (Robotics Innovation Center (RIC)) in Bremen, where I applied self-supervised learning techniques to underwater sonar and camera images focusing on underwater robot navigation and perception. Prior to that, I worked as a machine learning researcher at the Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) in Bonn, where I applied generative modeling to time series for unsupervised anomaly detection and 3D reconstruction of turbulent flows. I obtained my M.Sc. in Autonomous Systems from the University of Applied Sciences Bonn-Rhein-Sieg (Germany) and my B.Sc. in Physics from the Universidad Autonoma de Baja California (Mexico), I wrote my B.Sc. thesis at the National Metrology Institute of Germany (PTB) in the field of Trapped-Ion Quantum Engineering.
My research interests lie at the intersection of machine learning, optimization, and statistical modeling with broad applications to computer vision, time series, and telecommunications.