Francisco González
Director Of AI & Machine Learning at OneSix
Chicago, Illinois, United States
Summary
👤
Senior🎓
Top SchoolFrancisco Gonzalez is a Senior Machine Learning Scientist in Seattle with 10 years of experience building and deploying ML and computer vision products, currently leading AI/ML work at OneSix via Strong Analytics. Trained as an aerospace engineer with deep roots in computational physics and high-performance computing, he brings research-grade methods—such as convolutional recurrent autoencoders and transformer-based multi-view models—into production systems for vehicle claims automation and AR pose tracking. His academic work earned an NVIDIA GPU grant and resulted in open-source tooling for neural model order reduction, showing a habit of turning novel research into reusable software. Comfortable across multi-modal modeling, large-scale numerical experiments, and distributed runtimes, he blends rigorous simulation background with practical product delivery. Notably, his career spans national labs and industry, pairing publications and open-source contributions with tangible commercial impact.
10 years of coding experience
7 years of employment as a software developer
Master of Science, Aerospace Engineering, Master of Science, Aerospace Engineering at University of Illinois Urbana-Champaign
English, Spanish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (61)
turicreate10
simulation9
load-balancing9
asynchronous-tasks9
parallel-computing9
physics-informed-neural-networks9
hydrodynamics9
cpp9
computational-fluid-dynamics8
python8
deep-learning8
gpu8
segmentation8
dynamical-systems8
machine-learning8
Programming languages (5)
Github contributions (5)
panchgonzalez/panchgonzalez.github.io
Apr 2020 - Oct 2022
Personal website
Contributions:72 commits, 4 PRs, 102 pushes in 2 years 6 months
reactnextjs
panchgonzalez/nmor
Feb 2020 - Dec 2020
Deep learning framework for model reduction of dynamical systems
Contributions:3 commits, 9 pushes, 3 branches in 10 months
deep-learningdimensionality-reductiontensorflowscientific-computingdynamical-systems
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