DeepSpatial2020: 1st ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems San Diego, CA, United States, August 24, 2020 |
Conference website | http://mason.gmu.edu/~lzhao9/venues/DeepSpatial2020/ |
Submission link | https://easychair.org/conferences/?conf=deepspatial2020 |
Abstract registration deadline | May 20, 2020 |
Submission deadline | May 20, 2020 |
The significant advancements in software and hardware technologies stimulated the prosperities of the domains in spatial computing and deep learning algorithms, respectively. Recent breakthroughs in the deep learning field have exhibited outstanding performance in handling data in space and time in specific domains such as image, audio, and video. Meanwhile, the development of sensing and data collection techniques in relevant domains have enabled and accumulated large scale of spatiotemporal data over the years, which in turn has led to unprecedented opportunities and prerequisites for the discovery of macro- and micro- spatiotemporal phenomena accurately and precisely. The complementary strengths and challenges between spatiotemporal data computing and deep learning in recent years suggest urgent needs to bring together the experts in these two domains in prestigious venues, which is still missing until now.
This workshop will provide a premium platform for both research and industry to exchange ideas on opportunities, challenges, and cutting-edge techniques of deep learning in spatiotemporal data, applications, and systems.
Submission Guidelines
The following paper categories are welcome:
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Full research papers – up to 9 pages (8 pages at most for the main body and the last page can only hold references)
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Vision papers and short system papers - up to 5 pages (4 pages at most for the main body and the last page can only hold references)
All manuscripts should be submitted in a single PDF file including all content, figures, tables, and references, following the format of KDD conference papers. Paper submissions need to include author information (review not double blinded).
Papers should be submitted at: https://easychair.org/my/conference?conf=deepspatial2020
Concurrent submissions to other journals and conferences are acceptable. Accepted papers will be presented as posters during the workshop and posted on the website. Besides, a small number of accepted papers may be selected to be presented as contributed talks.
List of Topics (include but not limited to)
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Novel deep learning techniques for spatial and spatio-temporal data
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Spatial representation learning and deep neural networks for spatio-temporal data and geometric data
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Interpretable deep learning for spatial-temporal data
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Deep generative models for spatio-temporal data
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Deep reinforcement learning for spatio-temporal decision making problems
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Novel applications of deep learning techniques to spatio-temporal computing problems.
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Geo-imagery and point cloud analysis (for remote sensing, Earth science, etc.)
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Deep learning for mobility and traffic data analytics
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Location-based social network data analytics, spatial event prediction and forecasting
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Learning for biological data with spatial structures (bio-molecule, brain networks, etc.)
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Novel deep learning systems for spatio-temporal applications
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Real-time decision-making systems for traffic management, crime prediction, accident risk analysis, etc.
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Disaster management and respond systems using deep learning
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GIS systems using deep learning (e.g., mapping, routing, or visualization)
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Mobile computing systems using deep learning
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In addition, we encourage submissions of spatiotemporal deep learning methods that address problems related to the COVID-19 pandemic.
Committees
Program Committee
- Arnold Boedihardjo, DigitalGlobe
- Manzhu Yu, PSU
- Wei Wang, Microsoft Research
- Chao Zhang, Georgia Tech
- Yanjie Fu, CFU
- Xuchao Zhang, NEC Lab North America
- Ray Dos Santos, Army Corps of Engineers
- Yanhua Li, WPI
- Lingfei Wu, IBM Research
- Yinghui Wu, WSU
- Zhe Jiang, University of Alabama
- Kangkook Jee, UT Dallas
- Jing Dai, Google
Organizing committee
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Liang Zhao, George Mason University
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Xun Zhou, University of Iowa
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Feng Chen, University of Texas, Dallas
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Jieping Ye, University of Michigan & Didi Chuxing
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Shashi Shekhar, University of Minnesota
Venue
The workshop will be held in conjunction with KDD 2020. The format of the workshop will follow the decision of KDD 2020. It is quite possible that we will have an online workshop.
Contact
All questions about submissions should be emailed to:
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Liang Zhao (George Mason University, lzhao9@gmu.edu , 4400 University Drive, Fairfax, VA 22030)
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Xun Zhou (University of Iowa, xun-zhou@uiowa.edu, S280 PBB, Iowa City, IA 52242)
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Feng Chen (University of Texas at Dallas, feng.chen@utdallas.edu, ECSS 3.901 UTD, 800 W. Campbell Road, Richardson, TX 75080)