Portrait of Dr. Subasish Das

Dr. Subasish Das

  • Assistant Professor at Ingram School of Engineering, College of Science & Engineering

Biography

Dr. Subasish Das is an Assistant Professor of Civil Engineering Program in the Ingram School of Engineering at Texas State University. Previously, he worked as a full-time Associate Research Scientist at TTI during 2015 to 2022. He has more than 15 years of experience related to roadway safety, traffic operation, and connected and automated vehicle (CAV) technologies. He is a Systems Engineer by training with hands on experience on Six Sigma and Lean Engineering. His major areas of expertise include database management, statistical analysis and machine learning with emphasis in safety and transportation operations, spatial analysis with modern web GIS tools, interactive data visualization, and deep learning tools for CAV technologies. Dr. Das is a prolific author. He has published more than 220technical reports, and journal articles. He is the author of the book “Artificial Intelligence in Highway Safety,” which was published by CRC Press in 2022. The AASHTO Research Advisory Committee (RAC) awarded one of his research reports as 2014 AASHTO Sweet Sixteen High Value Research Project. Dr. Das is an active member of ITE, and ASCE. He is an Eno Fellow. He served as vice-president of membership of Young Professionals in Transportation Houston chapter. He is currently a member of three TRB Committees: Information and Knowledge Management (AJE45), Artificial Intelligence and Advanced Computing Applications (AED50), and Impairment in Transportation (ACS50).

Research Interests

Smart infrastructure
Connected and Automated Vehicles
Foundation Models
Artificial Intelligence (AI) and Causal AI
Traffic Safety and Operations
Natural Language Processing
Advanced Language Models
Digital Twin
GIS
Systems Engineering

Teaching Interests

Transportation Safety
Highway Engineering
Traffic Engineering
Transportation Planning
Infrastructure Resilience
Artificial Intelligence in Transportation
Machine Learning
Statistical Inference
Statistical Computing