Public Transportation Optimization

Oct 1, 2018
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Using a large volume of bus data in the form of GPS coordinates (over 100 million data points) and automated passenger count data (over 1 million data points) we have developed (1) a system of analysis and prediction of future public transportation demand (2) a new model that uses concepts specific to college campuses that maximizes passenger satisfaction. Using these concepts we improve service of a model college public transportation service and more specifically the Indiana University Campus Bus Service (IUCBS).

Big Data Data Science Public Transportation
Dr. Hasan Kurban
Dr. Hasan Kurban
Computer & Data Scientist

As a Computer Scientist and Machine Learning Researcher, I am passionate about developing intelligent systems that leverage data-driven approaches to address real-world challenges.