JSM2026
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Topic-Contributed Paper Session

Synthetic Data and AI Bias in Transportation

Sun, Aug 2, 2:00 PM - 3:50 PM Room CC-210A Thomas M. Menino Convention & Exhibition Center
Justin ChimkaOrganizerPatricia HuOrganizerJustin ChimkaChair
Transportation Statistics Interest Group co: No Additional Sponsorco: No Additional Sponsor Applied

5 Presentations

Computationally Efficient Learning of Artificial Intelligence System Reliability Considering Error Propagation
2:05 PM - 2:25 PM
Fenglian Pan (UNC Charlotte)
Co-authors: Fenglian Pan (UNC Charlotte)
Integrative Vehicle Safety through Fusion of Field and Synthetic Crash Data
2:25 PM - 2:45 PM
Wenbo Sun
Co-authors: Wenbo Sun
Integrative safetyADS simulationCrash data analysis
SynSHRP2: A Synthetic Multimodal Benchmark for Driving Safety-critical Events Derived from Real-world Driving Data
2:45 PM - 3:05 PM
Liang Shi (Virginia Tech)
Co-authors: Liang Shi (Virginia Tech)
Responsible Use of Data for AI
3:05 PM - 3:25 PM
Stuart Gluck (U.S. Department of Transportation)
Co-authors: Stuart Gluck (U.S. Department of Transportation)
Order Dependence in Synthetic Data Generated by Sequential Regression Models
3:25 PM - 3:45 PM
Justin Chimka (University of Arkansas)
Co-authors: Justin Chimka (University of Arkansas), Fardeen Islam (University of Arkansas, Fayetteville)
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