Home Categories About Call for Papers

DeepSpatial 2020 : 1st ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Sytems

San Diego, CA, USA

Event Date:	August 24, 2020 - August 24, 2020
Submission Deadline:	May 20, 2020
Notification of Acceptance:	June 15, 2020
Camera Ready Version Due:	June 20, 2020

About

Deep learning has exhibited outstanding performance in handling data in space and time in specific domains such as image, audio, and video. Meanwhile, the novel applications such as location-based social media, data-driven climate and Earth science, and ride-sharing 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. Further developments of spatial/spatiotemporal computing and deep learning call for the synergistic techniques and the collaborations between different communities, as evidenced by the recent momentum in both domains. On one hand, fast-increasing large-scale and complex-structured spatiotemporal data requires the investigation and extension toward more scalable and powerful models than traditional ones in domains such as computational geography and spatial statistics. One the other hand, deep learning techniques are evolving beyond regular grid-based (e.g., images), tree-based (e.g., texts), and sequence-based (e.g., audio) data to more generic or irregular data in space and time (e.g., in transportation, geomorphology, and protein folding), which calls for the expertise in the domains such as spatial statistics, geodesy, geometry, graphics, and geography. Consequently, the aforementioned 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.

Call for Papers

This workshop will provide a premium platform for researchers from both academia and industry to exchange ideas on opportunities, challenges, and cutting-edge techniques of deep learning for spatiotemporal data, applications, and systems. Papers will be accepted under the topics including, but not limited to, the following three broad categories:

Novel Deep Learning Techniques for Spatial and Spatio-Temporal Data:

Spatial representation learning and deep neural networks for spatio-temporal data and geometric data
Interpretable deep learning for spatial-temporal data
Deep generative models for spatio-temporal data
Deep reinforcement learning for spatio-temporal decision making problems

Novel Applications of Deep Learning Techniques to Spatio-temporal Computing Problems. :

Geo-imagery and point cloud analysis (for remote sensing, Earth science, etc.)
Deep learning for mobility and traffic data analytics
Location-based social network data analytics, spatial event prediction and forecasting
Learning for biological data with spatial structures (bio-molecule, brain networks, etc.)

Novel Deep Learning Systems for Spatio-temporal Applications:

Real-time decision-making systems for traffic management, crime prediction, accident risk analysis, etc.
GIS systems using deep learning (e.g., mapping, routing, or Smart city)
Mobile computing systems using deep learning
Interpretable deep learning systems for spatio-temporal temporal data

In addition, we encourage submissions of spatiotemporal deep learning methods that address problems related to the COVID-19 pandemic.

Summary

DeepSpatial 2020 : 1st ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Sytems will take place in San Diego, CA, USA. It’s a 1 day event starting on Aug 24, 2020 (Monday) and will be winded up on Aug 24, 2020 (Monday).

DeepSpatial 2020 falls under the following areas: DEEP LEARNING, DATA MINING, etc. Submissions for this Workshop can be made by May 20, 2020. Authors can expect the result of submission by Jun 15, 2020. Upon acceptance, authors should submit the final version of the manuscript on or before Jun 20, 2020 to the official website of the Workshop.

Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines.

Other Details of the DeepSpatial 2020

Short Name: DeepSpatial 2020
Full Name: 1st ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Sytems
Timing: 09:00 AM-06:00 PM (expected)
Fees: Check the official website of DeepSpatial 2020
Event Type: Workshop
Website Link: http://mason.gmu.edu/~lzhao9/venues/DeepSpatial2020/
Location/Address: San Diego, CA, USA

Credits and Sources

[1] DeepSpatial 2020 : 1st ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Sytems