Biography
Dr. Subasish Das is an Assistant Professor in the Civil Engineering Program at the Ingram School of Engineering, Texas State University. A systems engineer by training, his work advances roadway safety, traffic operations, and connected and automated vehicle (CAV) systems through data‑intensive methods. His expertise spans database engineering; statistical analysis and machine learning for safety and operations; spatial analytics with modern web GIS; interactive data visualization; and deep learning for CAV applications. He also brings hands‑on experience with Six Sigma and Lean engineering.
Prior to joining Texas State, Dr. Das served as an Associate Research Scientist at the Texas A&M Transportation Institute (2015–2022). He has authored more than 380 publications, including technical reports and journal articles, and is the author of two books: Artificial Intelligence in Highway Safety (CRC Press, 2022) and Urban Human MobilityPractices, Analytics, and Strategies for Smart Cities (CRC Press, 2025). His research received the AASHTO Research Advisory Committee “Sweet Sixteen” High‑Value Research recognition (2014). His other awards include: Eno Fellowship (2015), TTI Young Researcher Award (2017), TXST Research Millionaire Award (2024), and TXST CoSE Presidential Distinction Award for Excellence in Scholarly/Creative Activities (2025). Since 2015, Dr. Das has led research portfolios exceeding $7.42 million as PI/Co‑PI; since arriving at Texas State University in 2022, he has secured approximately $4.61 million, including five National Academies projects as principal investigator. He is an Eno Fellow and an active member of the Institute of Transportation Engineers (ITE) and the American Society of Civil Engineers (ASCE). He currently serves on the Transportation Research Board’s Committee on Integrated Transportation Safety Management (ACD11), previously served on AJE45, AED50, and ACS50, and chairs the User Liaison Subcommittee of ITE’s Data‑Driven Safety Analysis group. He is editor/handling editor of several journals including Transportation Research Record, Journal of Transportation Safety & Security, and Plos One.
Prior to joining Texas State, Dr. Das served as an Associate Research Scientist at the Texas A&M Transportation Institute (2015–2022). He has authored more than 380 publications, including technical reports and journal articles, and is the author of two books: Artificial Intelligence in Highway Safety (CRC Press, 2022) and Urban Human MobilityPractices, Analytics, and Strategies for Smart Cities (CRC Press, 2025). His research received the AASHTO Research Advisory Committee “Sweet Sixteen” High‑Value Research recognition (2014). His other awards include: Eno Fellowship (2015), TTI Young Researcher Award (2017), TXST Research Millionaire Award (2024), and TXST CoSE Presidential Distinction Award for Excellence in Scholarly/Creative Activities (2025). Since 2015, Dr. Das has led research portfolios exceeding $7.42 million as PI/Co‑PI; since arriving at Texas State University in 2022, he has secured approximately $4.61 million, including five National Academies projects as principal investigator. He is an Eno Fellow and an active member of the Institute of Transportation Engineers (ITE) and the American Society of Civil Engineers (ASCE). He currently serves on the Transportation Research Board’s Committee on Integrated Transportation Safety Management (ACD11), previously served on AJE45, AED50, and ACS50, and chairs the User Liaison Subcommittee of ITE’s Data‑Driven Safety Analysis group. He is editor/handling editor of several journals including Transportation Research Record, Journal of Transportation Safety & Security, and Plos One.
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
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
Highway Engineering
Traffic Engineering
Transportation Planning
Infrastructure Resilience
Artificial Intelligence in Transportation
Machine Learning
Statistical Inference
Statistical Computing