RESEARCH INTERESTS: Predictive Analytics, spatiotemporal modeling, machine learning for mobility & operations, digital twins & safety analytics, simulation-based optimization

Alican Sevim, Post-Doctoral Researcher - Dr. Sevim is a post-doctoral researcher in the Department of Civil and Environmental Engineering at the FAMU-FSU College of Engineering and the RIDER Center. His research lies at the intersection of intelligent transportation systems, machine learning, and mobility resilience, with a focus on predictive modeling, safety analytics, and digital-twin–enabled decision support. Dr. Sevim has supported and co-led federally funded research efforts and proposals totaling nearly $2 million, including projects sponsored by the National Science Foundation (NSF), U.S. Department of Transportation (DOT), Federal Motor Carrier Safety Administration (FMCSA), and INRIX. His work spans real-time vehicle safety modeling, autonomous mobility solutions, and digital twin systems, leveraging advanced methodologies such as machine learning, trajectory forecasting, spatiotemporal analytics, and simulation-based risk analysis. Through collaborations with government agencies (DOT, FMCSA), research institutions (MITRE, various universities), and industry partners, Dr. Sevim develops scalable analytical tools that enhance mobility resilience, optimize safety, and enable data-driven operational planning. With a multidisciplinary background that integrates engineering, data science, and project management, he builds system-level solutions that transform high-volume mobility data into actionable insights for smarter and more resilient decision-making in complex and uncertain environments.