Billy Charlton
Data Scientist Software Engineer
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolBilly Charlton is a data scientist and software engineer with 12 years of experience applying agent-based transport modeling, data visualization, and web development to improve urban mobility. Based in Berlin with a PhD from TU Berlin, he builds open-source tooling for MATSim and has directly contributed backend fixes and refactors to the widely used matsim-libs project, improving grid and emissions time-bin processing. A former Director of Data at the Puget Sound Regional Council and Deputy Director in San Francisco, he has led large multidisciplinary teams and delivered public-facing data products like the TNC visualizer for SFCTA. He combines deep transport planning domain expertise with hands-on software craftsmanship and a founder’s mindset from running Because LLC. Notably, he blends rigorous academic training with practical production work—shipping scalable visualization platforms that make complex travel models accessible to planners and the public.
12 years of coding experience
16 years of employment as a software developer
Doctor of Philosophy - PhD, Transport Telematics and Transport Planning, Magna cum Laude, Doctor of Philosophy - PhD, Transport Telematics and Transport Planning, Magna cum Laude at Technische Universität BerlinMaster of Science - MS, Civil Engineering, Master of Science - MS, Civil Engineering at Northwestern UniversityBachelor of Science - BS, Civil Engineering, Bachelor of Science - BS, Civil Engineering at Cornell University
English, German
Stackoverflow
68reputation
3kreached
1answer
1question
Github Skills (10)
simulations10
simulation10
javas10
agent10
java10
algorithms8
data-structures8
data-structure8
user-interface6
android6
Programming languages (14)
Github contributions (5)
matsim-org/matsim-libs
Jan 2019 - May 2019
Multi-Agent Transport Simulation
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 commits, 5 PRs, 4 pushes in 4 months
Contributions summary:Billy primarily worked on improving the `HexagonalGrid` and related grid calculations within the analysis contributions, fixing errors in the Y-distance and area calculations. The user also added new methods to retrieve time bins individually within the emissions contrib module. Furthermore, the user refactored the emissions contrib module by replacing the time bins processing mechanism with a new iterator-based one.
agent-basedtransportation-planningagentagent-based-modelmatsim
sfcta/tncstoday
Mar 2017 - Jun 2017
Tool for visualizing the estimate of number of TNC (Uber and Lyft) pickups and dropoffs in San Francisco—by location and by time of day.
Contributions:158 commits, 11 pushes, 1 branch in 2 months
lyftdaypickupsvisualizinglocation
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