Urban AI is an emerging field that combines AI, computing, and urban sciences to address complex challenges faced by cities. The availability of extensive urban data and the growth of digitized city infrastructures have opened opportunities for data-driven machine learning approaches in urban science. Urban AI encompasses innovative AI techniques applied to urban problems, AI-ready urban data infrastructure, and various urban applications benefiting from AI. Its applications range from urban planning and design to traffic prediction, energy management, public safety, urban agriculture, and land use. This workshop aims to bring together researchers and practitioners to discuss advancements and future directions in urban AI.

UrbanAI 2023 will be co-hosted with the 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2023, https://sigspatial2023.sigspatial.org/)

We solicit for regular papers (8-10 pages), short papers (4 pages), or position papers (2 pages) describing work-in-progress with innovative ideas related to the workshop topics. All papers must be original and not simultaneously submitted to another journal or conference.

Important Dates
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Full Paper Submission Deadline: September 15, 2023
Author Notification: October 6, 2023
Camera-Ready Copy: October 20, 2023
Workshop: November 13, 2023

Papers must be in ACM SIG format (US Letter size, 8.5 x 11 inches) including text, figures and references and submitted through EasyChair link: https://easychair.org/cfp/UrbanAI-2023. Accepted papers will be published in the ACM digital library under the condition that at least one author has registered for both the main SIGSPATIAL conference and the workshop, attends the workshop, and presents the accepted paper in the workshop. Otherwise, the accepted paper will not appear in the workshop proceedings or in the ACM Digital Library version of the workshop proceedings.

For more information, please visit the workshop website: https://urbanai.ornl.gov/urbanai2023/. Please email urbanai@ornl.gov if you have any questions.

Workshop Organizers
Dr. Femi Omitaomu
Group Leader, Computational Urban Sciences Group
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA.

Prof. Ali Mostafavi
Associate Professor and Faculty Director, UrbanResilience.AI Lab
Texas A&M University, College Station, Texas, USA.

Dr. Yan Liu
Computational Scientist, Computational Urban Sciences Group
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA.