Md Mobasshir Rashid, PhD, EIT

Dr. Rashid has four years of experience using Artificial Intelligence (AI) in transportation network modeling and traffic safety analysis. He is skilled in applying advanced ML and DL algorithms, along with statistical modeling and big data analytics, to solve complex transportation problems. He is interested in developing data-driven traffic forecasting models and AI-driven travel demand modeling techniques. 

Before joining Insight, Dr. Rashid was a member of the Urban Networks, Mobility and Dynamics (UNMD) lab at the University of Central Florida (UCF), where he collaborated on various research projects focusing on emergency disaster management, evacuation planning, incident management, and integrated corridor management (ICM). He has experience in developing traffic prediction models for general traffic, incident impacts, and hurricane evacuations, data analytics (using R and Python), geospatial data analysis (using ArcGIS and Python’s Geopandas library), and location-based data analysis from social media data. Dr. Rashid is also proficient in handling large-scale spatiotemporal datasets and deploying predictive models in real-world scenarios. 

Dr. Rashid holds a Master's degree in Civil Engineering from Florida State University and a PhD. in Transportation Engineering from the University of Central Florida.