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SMART-TWIN: Building a Digital Twin for Smarter Traffic Operations
Monday, November 16, 2026
Online
12:00-12:30p.m. (PT) | Link to register.
This MTI Research Snaps webinar is based on an MTI-led CSUTC research project, SMART-TWIN: Systematic Modeling and Real-Time Transportation with Digital Twins.
Transportation agencies need to make faster, smarter decisions about congestion, safety, and infrastructure, often with limited resources and incomplete information. Digital Twins offer a way to move beyond traditional traffic simulation by connecting modeled conditions with real-time operational insights. In this webinar, attendees will learn about SMART-TWIN, an AI-powered Digital Twin designed to help agencies identify traffic problems early and understand their real-world impacts. Using a Fresno corridor as a case study, the research shows how SMART-TWIN can help agencies identify traffic disruptions, understand their impacts, and make faster, better-informed decisions.
Featured Guest: Hovannes Kulhandjian, PhD, MTI Researcher & Professor, California State University, Fresno
Moderator: Hilary Nixon, PhD, Deputy Executive Director, Mineta Transportation Institute (MTI)
*0.5 PDH credit available
About the Featured Guest
Hovannes Kulhandjian, PhD, is a Professor of Electrical and Computer Engineering at California State University, Fresno. His research focuses on artificial intelligence, intelligent transportation systems, Digital Twins, autonomous robotics, and smart infrastructure. He developed SMART-TWIN, an AI-driven Digital Twin framework for real-time traffic operations and infrastructure decision-making, and CrossBot, an AI-powered autonomous crossing guard robot that has received local, national, and international media attention for its innovative approach to improving pedestrian safety. Dr. Kulhandjian is an IEEE Senior Member and IEEE Distinguished Lecturer committed to advancing AI-driven technologies for safer and more efficient transportation systems.
Presenters:
Hovannes Kulhandjian, PhD
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