Matthew Battifarano is a Senior Data Scientist with 11 years of experience applying statistics, machine learning, and game-theoretic network equilibrium theory to transportation and urban systems. He blends rigorous academic research from Carnegie Mellon’s Mobility Data Analytics Center—where he developed novel methods to infer traveler reward signals and modeled impacts of optimized fleets—with hands-on engineering shipping real-time routing and forecasting systems at Bridj and Aurora. Comfortable at the intersection of research and production, he has implemented cloud-native simulators, surge-prediction models, and fleet optimization engines that influenced strategy and operations. An active contributor to the Rust geospatial ecosystem (improving the widely used geo crate), he brings both algorithmic depth and low-level systems craftsmanship. Based in Pittsburgh, he’s especially focused on how shared, connected, and autonomous mobility reshape congestion and market dynamics.
11 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Advanced Infrastructure Systems, Doctor of Philosophy - PhD, Advanced Infrastructure Systems at Carnegie Mellon University
BA, Mathematics, BA, Mathematics at The University of Chicago
Contributions:25 commits, 5 PRs, 27 comments in 8 months
Contributions summary:Matthew primarily focused on improving the `geo` crate, a Rust library for geospatial primitives and algorithms. Their contributions included refactoring the `Polygon` struct with named parameters and implementing various trait implementations. They added and enhanced functionality for `Line` and improved the library's ability to handle intersection and containment tests. The user also added tests for the new functionality.
Contributions:2 reviews, 4 PRs, 31 pushes in 4 years 7 months
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