Data-enabled smart transportation has attracted a surge of interest from machine learning and data mining communities nowadays due to the bloom of online ride-hailing industry and rapid development of intelligent driving. Large-scale high quality route data and trading data (spatiotemporal data) have been generated every day, which makes AI a natural choice for the decision making in intelligent transportation systems. While a large of amount of work has been dedicated to traditional transportation problems, they are far from satisfactory for the rising need.
We propose a half-day workshop at CIKM 2019 for the professionals, researchers, and practitioners who are interested in mining and understanding big and heterogeneous data generated in transportation, and AI applications to improve the transportation system.
Room 303B, China National Convention Center
2:00 PM - 5:00 PM
November 7th, 2019
2:00 PM - 2:10 PM -- Opening & Welcome
2:10 PM - 2:40 PM -- Keynote Talk: Towards Real-world Decision-Making via Simulator-based Reinforcement Learning
Dr. Yang Yu, Professor, LAMDA Group, School of Artificial Intelligence, Nanjing University
2:40 PM - 3:10 PM -- Keynote Talk: Team Competition Promotes Productivity in Ride-sharing Economy
Dr. Qiaozhu Mei, Professor, School of Information, Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor
3:10 PM - 3:40 PM -- Keynote Talk: Multi-agent Reinforcement Learning for Complex Optimization
Dr. Bo An, Associate Professor, School of Computer Science and Engineering, Nanyang Technological University
3:40 PM - 4:00 PM -- Coffee Break
4:00 PM - 4:45 PM -- Contributed Talks
4:45 PM - 5:00 PM -- Concluding Remarks
Yang Yu is a Professor of School of Artificial Intelligence in Nanjing University, China. His research interest is mainly in reinforcement learning. He was recommended as "AI’s 10 to Watch" by IEEE Intelligent Systems in 2018, invited to have an Early Career Spotlight talk in IJCAI’18 on reinforcement learning, and received the Early Career Award of PAKDD in 2018.
University of Michigan, Ann Arbor
Qiaozhu Mei is a professor in the School of Information and the Department of EECS at the University of Michigan. His research focuses on large-scale data mining, machine learning, information retrieval, and natural language processing, with broad applications to social media, Web, and health informatics. Qiaozhu is an ACM distinguished member (2017) and a recipient of the NSF Career Award (2011). His work has received multiple best paper awards at ICML, KDD, WWW, WSDM, and other major conferences in computing. He has served as the General Co-Chair of SIGIR 2018 and is on the editorial boards of multiple journals such as JMLR, TOIS, and TWEB. He is the founding director of the new master degree of applied data science at the University of Michigan.
Nanyang Technological University
Bo An is the President’s Council Chair Associate Professor in Computer Science and Engineering, Nanyang Technological University. He received the Ph.D degree in Computer Science from the University of Massachusetts, Amherst. His current research interests include artificial intelligence, multiagent systems, computational game theory, reinforcement learning, and optimization. His research results have been successfully applied to many domains including infrastructure security and e-commerce. He has published over 100 referred papers at AAMAS, IJCAI, AAAI, ICAPS, KDD, WWW, JAAMAS, NeurIPS, AIJ and ACM/IEEE Transactions. Dr. An was the recipient of the 2010 IFAAMAS Victor Lesser Distinguished Dissertation Award, an Operational Excellence Award from the Commander, First Coast Guard District of the United States, the 2012 INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice, and 2018 Nanyang Research Award (Young Investigator). His publications won the Best Innovative Application Paper Award at AAMAS’12 and the Innovative Application Award at IAAI’16. He was invited to give Early Career Spotlight talk at IJCAI’17. He led the team HogRider which won the 2017 Microsoft Collaborative AI Challenge. He was named to IEEE Intelligent Systems' "AI's 10 to Watch" list for 2018. He was invited to be an Advisory Committee member of IJCAI’18. He is PC Co-Chair of AAMAS’20. He is a member of the editorial board of JAIR and the Associate Editor of JAAMAS, IEEE Intelligent Systems, and ACM TIST. He was elected to the board of directors of IFAAMAS and senior member of AAAI.
In this workshop, we invite professionals, researchers and technologists of all relevant fields to present the state-of-the-art development and applications, share their envisions about the future of intelligent transportation informatics.
The topics of interests include, but not limited to, the following aspects:
We encourage short papers (4 pages), poster papers (2 pages) and demo proposals (2 pages). Submissions of workshop papers must be in English, in PDF format, and should not exceed the appropriate length requirements in the current ACM two-column conference format. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this workshop. We will follow a single-blind process and submissions will be evaluated by the program committee based on the quality of the work and its fit to the workshop themes. All papers are to be submitted via EasyChair a link here .
For inquires about the workshop and submissions, please email to an email here
June 1, 2019: all invited keynotes and research talks are confirmed.
September 5, 2019: Workshop paper due. (Anywhere on Earth)
September 20, 2019: Workshop paper notifications.
November 7, 2019: Workshop Day.
Notice: The date of Workshop paper due has been postponed to September 5, 2019.