Francisco Gonzalez

Francisco González Arellano has a diverse work experience in the field of machine learning and research. From 2019 to present, they have been working at Strong Analytics, initially as a Machine Learning Scientist and later as a Senior Machine Learning Scientist. Prior to that, from 2018 to 2019, they worked as a Computer Vision Data Scientist at CCC Intelligent Solutions.

Before transitioning to industry, Francisco gained valuable research experience. From 2016 to 2018, they worked as a Graduate Research Assistant at the University of Illinois at Urbana-Champaign, where they focused on deep learning applications in computational fluid mechanics. During this time, they developed a novel convolutional recurrent autoencoder architecture for reduced-order modeling in complex fluid systems. Additionally, they also contributed to open-source projects related to neural model order reduction.

In 2018, Francisco interned as a Graduate Research Intern at Mitsubishi Electric Research Laboratories, and in 2016, they interned as a Graduate Research Intern at Los Alamos National Laboratory. At Los Alamos, they researched the applications of Charm++ asynchronous runtime system in finite element methods and contributed to an open-source package called Quinoa, which is a set of tools for asynchronous numerical methods in fluid dynamics.

Overall, Francisco's work experience showcases their expertise in machine learning, computer vision, and deep learning, as well as their proficiency in conducting research and contributing to open-source projects.

Francisco González Arellano has a strong educational background in aerospace engineering. From 2016 to 2018, they attended the University of Illinois Urbana-Champaign as a PhD student in Aerospace Engineering. During the same period, they also obtained a Master's Degree in Aerospace Engineering from the same institution. Prior to this, from 2012 to 2016, Francisco completed their Bachelor's Degree in Aerospace Engineering at the University of Illinois Urbana-Champaign.