Quantitative Analysis of Large-Scale Behavioral Data

My work in this area focuses on applying advanced quantitative and emerging statistical methods to analyze large-scale, real-world behavioral data. A fun example of this is my research into the societal impact of the mobile game Pokémon Go. This project involved analyzing a stated-preferences survey responses of player activity to rigorously test hypotheses about the game's influence on physical health and behavior.

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Another example of exciting paper is one, where we tried to forecasting the adoption of future technologies. In that work , we have developed models that account for user heterogeneity to better understand and predict consumer adoption patterns and fuel choices.

 

My research in transportation safety has involved applying advanced, random-parameter hazard models to analyze the temporal instability of environmental factors on accident occurrences, providing a deeper understanding of risk during events like snowstorms. This study is a motivation for another research trust that I am developing with my students at the moment. It includes building information system that utilizes Vesicle-to-infrastructure and vehicle-to cloud technologies to facilitate winter driving and road maintenance. Stay tuned for more details!