ACM SIGKDD dissertation awards recognize outstanding work done by graduate students in the areas of data science, machine learning and data mining. 

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KDD 2020 Will Convene in San Diego, California Aug. 22-27, 2020

KDD 2020 Will Convene in San Diego, California Aug. 22-27, 2020

ANCHORAGE, Alaska, Aug. 14, 2019  -- The Association for Computing Machinery (ACM) Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) today announced the location for KDD 2020, the group's flagship conference. The premier interdisciplinary data science conference will take place

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2019 SIGKDD Service Award: Balaji Krishnapuram

Balaji Krishnapuram, director and distinguished engineer at IBM Watson Health, is honored for his contributions to society through the development of machine learning products to improve healthcare. ACM SIGKDD Service Award is the highest service award in the field of knowledge discovery and data mining (KDD). It is conferred on one individual or one group for their outstanding professional services and contributions to the field of knowledge discovery and data mining.

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2019 SIGKDD Innovation Award: Dr. Charu Aggarwal

ACM SIGKDD is pleased to announce that Dr. Charu Aggarwal is the winner of its 2019 Innovation Award. He is a distinguished research staff member at IBM T.J. Watson Research Center and is recognized for his research contributions in high-dimensional data, privacy, data streams, uncertain data, graphs, text mining and social networks.

The ACM SIGKDD Innovation Award is the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD). It is conferred on one individual or one group of collaborators whose outstanding technical innovations in the KDD field have had a lasting impact in advancing the theory and practice of the field. The contributions must have significantly influenced the direction of research and development of the field or transferred to practice in significant and innovative ways and/or enabled the development of commercial systems.

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