KDD 2020 Call for Research, Applied Data Science Papers
ACM SIGKDD Invites Industry and Academic Experts to Submit Advancements in Data Mining, Knowledge Discovery and Machine Learning for 26th Annual Conference in San Diego.
KDD 2020 Opens Call for Research and Applied Data Science Paper Submissions
SAN DIEGO, Dec. 3, 2019—The Association for Computing Machinery’s (ACM) Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) today announced that KDD 2020, the premier interdisciplinary conference in data science, has opened the call for papers in both its research and applied data science tracks. KDD 2020 welcomes submissions on all aspects of knowledge discovery and data mining, from theoretical research on emerging topics to papers describing the design and implementation of systems for practical tasks. Topics of interest include artificial intelligence, big data, data analytics, data science, data mining, deep learning, knowledge graphs, machine learning, relational databases and statistical methods.
KDD 2020 is a dual-track conference, offering distinct programming in research and applied data science. The research track highlights innovative contributions to research in big data, data science and foundations, spanning theoretical foundations to novel models and algorithms for data mining challenges in business, engineering, medicine, science and more. The applied data science track focuses on the application of data mining, machine learning and statistics in addressing real-world challenges and enterprise systems with a tangible impact on industries, government initiatives and social programs. Key dates for applications in both tracks include:
- Submission Deadline: February 13, 2020
- Notification of Selection: May 15, 2020
- KDD 2020 in San Diego: Aug. 22-27, 2020
All papers submitted to KDD 2020 are reviewed by an all-volunteer team of more than 800 data science professionals. This year, Heng Huang, professor of electrical and computer engineering and biomedical informatics at University of Pittsburgh, and Wei Wang, professor of computer science and computational medicine at University of California Los Angeles, will lead the review process as the research track chairs. Suju Rajan, senior director of artificial intelligence at LinkedIn; Mohak Shah, vice president of artificial intelligence and machine learning at LG Electronics; and Yangqing Jia, vice president of engineering at Alibaba Group, will serve as chairs of the applied data science track.
In 2019, a record 1,808 papers from 7,966 authors at 1,200 organizations across 58 countries were submitted for KDD conference consideration. Maintaining its status as a highly selective showcase of the field’s best work, just 321 papers, or 17%, were accepted for publication. As data science continues to drive transformation throughout society, increased interest in the conference highlights the depth, breadth and impact of innovation in knowledge discovery and data mining.
About ACM SIGKDD:
ACM is the premier global professional organization for researchers and professionals dedicated to the advancement of the science and practice of knowledge discovery and data mining. SIGKDD is ACM’s Special Interest Group on Knowledge Discovery and Data Mining. The annual KDD International Conference on Knowledge Discovery and Data Mining is the premier interdisciplinary conference for data mining, data science and analytics.
Havas Formula for KDD 2020