Machine Learning in Science and Engineering Conference - Towards Relational AI: The Good, the Bad, and the Ugly of Learning over Networks

Presented on June 10, 2019 at 12:15 p.m. in the Georgia Tech Hotel and Conference Center, Georgia Institute of Technology.The second-annual Machine Learning in Science and Engineering (MLSE) Conference highlights advances in research that utilize methods of artificial intelligence, the development of new machine learning algorithms designed for science and engineering problems, and the ways these methods lead to innovations across various fields. Researchers from academia, government, and industry will gather to explore the future of research in science and engineering.PLENARY TALK - Jennifer Neville is the Miller Family Chair Associate Professor of Computer Science and Statistics at Purdue University. She received her Ph.D. from the University of Massachusetts Amherst in 2006. She is currently an elected member of the AAAI Executive Council. She was PC chair of the 9th ACM International Conference on Web Search and Data in 2016 and is PC chair for the SIAM International Conference on Data Mining in 2019. In 2012, Neville was awarded an NSF Career Award; in 2008, she was chosen by IEEE as one of “AI's 10 to watch;” and in 2007, was selected as a member of the DARPA Computer Science Study Group. Her work, which includes over 100 peer-reviewed publications with more than 5000 citations, focuses on developing data mining and machine learning techniques for complex relational and network domains, including social, information, and physical networks.Runtime: 66:03 minute