We are pleased to announce that a Carnegie Mellon, Machine Learning and Computer Science led team has been awarded SIG-KDD 2019 Test of Time paper award, for their paper: Cost-effective Outbreak Detection in Networks [.pdf] which was authored by Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne VanBriesen and Natalie Glance.
The SIGKDD Test of Time award recognizes outstanding papers from past KDD Conferences beyond the last decade that have had an essential impact on the data mining research community.
The first four authors were Ph.D. students, or faculty at the Machine Learning Department, or Computer Science Department at the time, while Professor VanBriesen is faculty with the College of Engineering, Department of Engineering at Public Policy. The paper gives general algorithms to quickly spot outbreaks, in a broad spectrum of networks, like news in blog information networks, or poison attacks in water-distribution networks.
Congratulations to the well-deserved recipients, Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne VanBriesen and Natalie Glance. Further information on the SIG-KDD Test of Time awards can be found on KDD’s website.