Building an understanding of how drivers interact with emerging vehicle technologies
The MIT Advanced Vehicle Technology Consortium provides data-driven insights into driver behavior, along with trust in AI and advance vehicle technology.
The MIT Advanced Vehicle Technology Consortium provides data-driven insights into driver behavior, along with trust in AI and advance vehicle technology.
United Kingdom Supply Chain and Logistics Excellence Centre (UK SCALE) joins prestigious international network to advance global supply chain and logistics innovation.
A cherished colleague, Byrnes left an “immense” legacy as a key member of MIT CTL’s education programs for more than 30 years.
Exceptional students from top programs across the US receive tuition fellowships and conditional acceptance to the MIT Supply Chain Management master’s program.
MIT has been a world leader in supply chain management education and research for more than five decades.
Annual awards from the MIT Center for Transportation and Logistics provide financial support to graduate students in logistics, supply chain management, and freight transportation areas.
In a new book, the founder of MIT’s Center for Transportation and Logistics examines how increasingly automated industries can sustain jobs.
Smith, in discussion with Center for Transportation and Logistics Director Yossi Sheffi, reflects on 50 years in business and building for the future.
In his research, Josué C. Velázquez Martínez focuses on logistics sustainability and small firms in emerging markets.
Digital Credentials Consortium’s new report explores barriers to adoption.
The PhD student seeks to improve patient care by helping facilities use their limited resources more effectively.
Washington is recognizing that the American truck driver shortage might have been misdiagnosed.
“A Shot in the Arm,” a new book from Professor Yossi Sheffi, reveals lessons about overcoming global threats.
Wise Systems has grown from an MIT class project to a company helping multinationals improve last-mile logistics.
Competing research teams trained machine learning models to predict optimal routing based on real field datasets.