T3D: A Comprehensive Data Dashboard for Time, Travel, and Telework

Date and time: July 23, 2024 | 11:00 am – 12:15 pm (CDT)

Speaker: Irfan Batur, PhD

Moderator: Ram M. Pendyala, PhD

Commentator: Steven E. Polzin, PhD

Registration: https://tinyurl.com/4bwzyt42

Archive: Flier | Recording

About the talk

The TOMNET and TBD University Transportation Centers are pleased to present the Time Use, Travel, and Telework Dashboard (T3D), an open source web-based platform that provides access and convenient analysis capabilities for the American Time Use Survey (ATUS) data series. Featuring dedicated pages for time use, travel, and telework, T3D empowers users to explore patterns and trends, conduct within-year and between-year analyses, and perform cross-segment studies for a comprehensive understanding of evolving trends in how Americans allocate their time, work, and travel on a daily basis. Join us for a webinar to learn more about the T3D platform and its many features and capabilities. The webinar will be presented by Dr. Irfan Batur, the principal investigator for the T3D development project, and moderated by Dr. Ram Pendyala with a special commentary by Dr. Steven Polzin.


Irfan Batur, PhD

Assistant Research Professor | Arizona State University, Tempe, Arizona, USA

Dr. Irfan Batur is an Assistant Research Professor in the School of Sustainable Engineering and the Built Environment at Arizona State University. He holds a PhD in Civil, Environmental, and Sustainable Engineering from Arizona State University, an MS in Industrial and System Engineering from Istanbul Sehir University, and a BS in Industrial Engineering from TOBB Economy and Technology University. Additionally, Dr. Batur is a member of the Transportation Research Board’s Committee on Travel Behavior and Values (AEP30) and serves as the Assistant Director at both the TOMNET University Transportation Center and TBD National Center. His research interests include travel behavior, sustainable and equitable transportation, emerging transportation technologies, travel demand forecasting, smart cities, and machine learning.

Scroll to Top