My research interests are broad and interdisciplinary, encompassing Urban Mobility Data Analytics, Spatiotemporal Data Modeling, Deep Learning and Artificial Intelligence, and Connected Automated Vehicles (CAV) and Cooperative-ITS. I am particularly driven by the desire to optimize urban mobility and contribute to the development of a sustainable and efficient urban transportation system. My work involves utilizing data analytics to draw valuable insights from urban mobility data and applying cutting-edge AI technologies in the field of transportation.
My research topics and interests are as follows:
Urban transportation and mobility data analytics Spatiotemporal data modeling (forecasting, imputation) Generative AI for transportation and mobility data Modeling CAV, C-ITS using Reinforcement Learning Other applications of machine learning and deep learning in the transportation domain
20172024
Research activity per year
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