Source: insidehpc.com
The Association for Computing Machinery’s Special Interest Group on Knowledge Discovery and Data Mining (ACM SIGKDD) will hold its flagship annual conference, KDD 2020, virtually, August 23-27. The KDD conference series, started in 1989, is the world’s oldest and largest data mining conference, and is the venue where concepts such as big data, data science, predictive analytics and crowdsourcing were first introduced. Continuing this tradition, KDD 2020 will showcase leading-edge research papers in data science, data mining, knowledge discovery, large-scale data analytics and big data. Despite being a fully virtual event, KDD 2020 will include all the same program offerings as previous years, including exciting keynote addresses, topical panels, invited talks, highly selective research and applied data science papers, informative and hands-on tutorials, and workshops.
“KDD is a ‘must attend’ conference, where the theory and practice in data science, machine learning and artificial intelligence come together in industry-defining innovations,” explained KDD 2020 General Co-chair Rajesh K. Gupta, University of California, San Diego. “Initially we had hoped that at least a portion of the conference could be ‘in-person,’ but ultimately we decided a fully virtual conference would be the safest option for our community. While organizing a fully virtual conference is unchartered territory, we have made sure all of the program facets from previous years will be part of KDD 2020–from fascinating keynote addresses, to engaging research, workshops and panels. We’ve planned an outstanding program and we are confident we will have record conference registrations.”
“Data science has exploded in the last 30 years and is now reshaping so many different disciplines,” added KDD 2020 General Co-chair Yan Liu, University of Southern California. “An example of this is KDD 2020’s Applied Data Science Invited Speakers track, which we are particularly excited about. This year, we have a roster of 18 leading practitioners in the field, working at companies such as Siemens, Microsoft, Facebook, Google, Amazon and Uber, among many others.”
