Rafael Bidese
Senior Data Scientist
Greater Indianapolis United States
Summary
👤
Senior🎓
Top SchoolRafael Bidese is a Senior Data Scientist with eight years of experience applying computer vision and machine learning to real-world agricultural and biological problems. He blends hands-on engineering—from embedded systems and IoT platform development to cloud and edge-deployable vision models—with academic rigor from a PhD in Biological/Biosystems Engineering and a postdoctoral AI fellowship. At Corteva he architected field-oriented imaging pipelines and won a Breakthrough Innovation Award for a 7x faster, +20% more accurate insect classifier, while his USDA work advanced self-supervised representations and applied foundational models like SAM and CLIP to phenomics. Comfortable leading distributed teams and coordinating complex data collection across time zones, he also co-founded an IoT startup that scaled to 40 clients and 400+ sensors. Rafael’s background in electronics and firmware gives him uncommon end-to-end fluency—able to design hardware, collect novel sensor modalities, and productionize ML models for research and operations.
8 years of coding experience
9 years of employment as a software developer
Technical Specialization Electronic Product Development, Technical Specialization Electronic Product Development at IFSC - Instituto Federal de Santa CatarinaVisiting Student Electrical and Electronics Engineering, Visiting Student Electrical and Electronics Engineering at Rice UniversityDoctor of Philosophy - PhD Biological/Biosystems Engineering, Doctor of Philosophy - PhD Biological/Biosystems Engineering at Auburn UniversityMaster’s Degree Electrical and Electronics Engineering, Master’s Degree Electrical and Electronics Engineering at Universidade Federal de Santa CatarinaPostdoctoral Fellowship Artificial Intelligence in Natural Sciences, Postdoctoral Fellowship Artificial Intelligence in Natural Sciences at Cornell University
English, Portuguese, Spanish
Github Skills (12)
estimate9
regression6
machine-learning4
trunk4
semi-supervised-learning4
pytorch3
anomaly-detection3
optimization2
differentiation2
deep-learning2
automatic-differentiation1
autodiff1
Programming languages (4)
Github contributions (5)
rafaelbidese/LumberjackNet
Apr 2020 - Feb 2022
This network uses MFCCs as features for a CNN to perform regression to estimate the diameter of pine tree's trunk during harvesting.
Contributions:14 commits, 12 pushes, 1 branch in 1 year 10 months
regressionharvestingmachine-learningdiameterpine
rafaelbidese/rafaelbidese.github.io
Mar 2021 - Feb 2023
Contributions:150 commits, 97 pushes, 1 branch in 1 year 10 months
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