The IEEE International Conference on Data Engineering (ICDE) addresses research issues in designing, building, managing, and evaluating advanced data-intensive systems and applications. It is a leading forum for researchers, practitioners, developers, and users to explore cutting-edge ideas and to exchange techniques, tools, and experiences. The 36th ICDE will be held in Dallas Texas, April 20-24, 2020. This award enables diverse US students to participate in ICDE-2020, provides opportunities to the students to interact with other attendees and attend the educational events being offered. The students' participation in ICDE-2020 is important to the students research training and will develop the future generation of leaders and workforce in the increasingly critical data management field.

The supported students will have opportunities to showcase their research results, learn about the cutting edge research conducted by others, and interact with experts at a premier data engineering conference. ICDE-2020 includes a comprehensive program including research papers presentations, tutorials, panels, industrial papers, and technical demonstrations that provide a platform for exchange of research results and ideas, interaction and education. The program also includes workshops that demand dedicated coverage due to their relevance to the current data management research and development, industrial exhibits, and keynote talks by leaders in academia and industry. The students will also have an opportunity to participate in a PhD Symposium, which provides a forum for PhD students to present their research ideas, and interact with and receive feedback from senior members of the research community in academia and industry. The focus of the PhD Symposium is on mentorship and providing constructive feedback to the students. These opportunities will have a long lasting impact on the future career of the participants.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Science Foundation (NSF)
Division of Information and Intelligent Systems (IIS)
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Sylvia Spengler
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University of Texas at Dallas
United States
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