Ferdinand Briones
Lecturer at University of the Philippines Diliman
Novi, Michigan, United States
Summary
👤
Senior🎓
Top SchoolFerdinand Briones is an electrical and computer engineering professional with a decade of experience bridging academia, research, and industrial data science. He teaches introductory programming and operating systems at the University of the Philippines while leading automation and control systems work for Morph Microfactories, where he helped develop robotics-enabled manufacturing for fiber-reinforced composites. His career includes applied deep learning and computer vision research, plus senior data science roles at UnitedHealth Group and Theoria Medical, evidencing a track record of moving models from research into production. A summa cum laude computer engineering graduate and MS candidate at UP Diliman, he combines strong academic credentials with hands-on systems engineering. Based in Novi, Michigan, Ferdinand brings an unusual mix of classroom pedagogy, patent-driven manufacturing innovation, and healthcare data science experience.
9 years of coding experience
8 years of employment as a software developer
Master of Science - MS, Electrical Engineering, Master of Science - MS, Electrical Engineering at University of the Philippines DilimanHigh School, 1st Honorable Mention, High School, 1st Honorable Mention at Manila Science High SchoolAteneo de Manila University
Github Skills (31)
representations8
representation-learning8
unsupervised-learning7
contrastive-learning6
torchvision5
cryptocurrency5
simple-framework5
machine-learning5
pytorch4
trading4
backtest4
deep-learning4
algotrading3
python3
quantitative-finance3
Programming languages (4)
Github contributions (5)
fjbriones/coe197-project
May 2017 - Oct 2017
Contributions:17 commits, 13 pushes, 1 branch in 5 months
fjbriones/deep-text-recognition-benchmark
May 2021 - Jul 2021
Text recognition (optical character recognition) with deep learning methods.
Contributions:80 pushes, 1 branch in 1 month
optical-character-recognitiontext-recognitiondeep-learningrecognitionoptical
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