Mario Bergés
Associate Professor
Pittsburgh, Pennsylvania, United States
Summary
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Senior🎓
Top SchoolMario Bergés is an associate professor at Carnegie Mellon University with a decade-long track record in instrumenting civil infrastructure to boost resilience, adaptiveness, and self-monitoring. He specializes in cost-effective sensor networks, data acquisition, and applying machine learning to signal processing for infrastructure and building energy management. His work bridges hands-on engineering—designing sensors and electricity monitoring systems—with data-driven insights that turn easy-to-obtain measurements into actionable decisions for highways and buildings. Trained with a Ph.D. in Advanced Infrastructure Systems, he combines academic rigor with industry experience from project management and construction roles, giving him a practical edge in deployment and field instrumentation. Notably, he focuses on extracting maximal value from low-cost sensors, a pragmatic approach that accelerates scalable monitoring without relying on expensive instrumentation.
10 years of coding experience
5 years of employment as a software developer
B.S., Civil Engineering, B.S., Civil Engineering at Instituto Tecnológico de Santo DomingoM.S., Civil and Environmental Engineering, M.S., Civil and Environmental Engineering at Carnegie Mellon University
Portuguese, Spanish
Github Skills (9)
energy8
data-driven7
machine-learning5
algorithms4
python4
forecast3
reinforcement-learning3
monitoring3
forecasting3
Programming languages (3)
Github contributions (5)
marioberges/F16-12-752
Oct 2016 - Dec 2016
Fall 2016 version of 12-752: Data-Driven Building Energy Management
Contributions:43 commits, 34 pushes, 1 branch in 1 month
marioberges/courses_12-752
Oct 2015 - Dec 2015
Contributions:63 commits, 4 PRs, 58 pushes in 1 month
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