On May 10, 2017 an internal symposium titled Machine Learning in Science and Engineering was held at Carnegie Mellon University to identify ways in which these computational tools are advancing a diversity of fields. Based on the strong response at CMU, an open conference on June 6-8, 2018 at the CMU campus in Pittsburgh will be hosted in partnership with Georgia Tech. This conference will survey advances in basic research that utilizes methods of artificial intelligence, the development of new machine learning algorithms designed for science and engineering problems, and ways that these methods are leading to innovations across these fields. Researchers from academia, government, and industry are invited to join us for a unique and fascinating forum on the future of research and innovation in science and engineering.

CMU Co-organizers

Newell Washburn (Chemistry/BME)
Elizabeth Holm (MSE)
Rachel Mandelbaum (Physics)
Diana Marculescu (ECE)
Barnabas Poczos (Machine Learning)
Aarti Singh (Machine Learning)

Georgia Tech Co-organizers

Dana Randall (Computer Science/Math)
Justin Romberg (ECE)
Deirdre Shoemaker (Physics)
David Sherrill (Chemistry)