Leonardo Bastos

Associate Professor

Rio de Janeiro, Brazil
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Summary

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Senior
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Top School
Leonardo Bastos is an Associate Professor and industrial engineer with a PhD who applies machine learning, causal inference, and operations research to improve decision-making in healthcare and oil & gas. He directs the NOIS lab at PUC‑Rio and combines academic leadership with hands‑on consulting at Tecgraf, delivering data-driven products and generative AI solutions for complex operational problems. His research portfolio spans predictive modeling, performance benchmarking, and evaluation of health systems—work supported by grants from institutions like the Bill & Melinda Gates Foundation and Pfizer. He contributes to international collaborations such as ISARIC at the University of Oxford and has led projects detecting epidemic outbreaks and improving intensive care analytics for Brazil’s SUS. Known for translating messy data into actionable knowledge, he brings an uncommon blend of field experience, industrial systems background, and applied AI expertise to bridge research and real-world impact.
code8 years of coding experience
job6 years of employment as a software developer
bookBachelor's Degree, Industrial Engineering, Bachelor's Degree, Industrial Engineering at Universidade do Estado do Pará
bookPontifical Catholic University of Rio de Janeiro
bookPhD Exchange program, PhD Exchange program at University of Amsterdam
bookExchange Study Program, Industrial Engineering, Exchange Study Program, Industrial Engineering at University of Windsor
languagesPortuguese, English, Spanish
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Github Skills (3)

in-progress6
testing4
machine-learning3

Programming languages (1)

R

Github contributions (5)

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Data for the paper "App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning" This work is in progress and under review.
Contributions:1 PR, 11 pushes in 2 years 6 months
in-progresstestingmachine-learningreviewstrategy
Contributions:8 pushes, 1 branch in 4 years 1 month
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Leonardo Bastos - Associate Professor