In recent years the field of machine learning has seen an incredible surge of interest. From image classifiers to board games, machine learning and big data and internet are making large impacts in nearly every field. Chemistry and Materials science is no different. Machine learning and informatics techniques have demonstrated strong success with property classification and materials design, facilitating extremely high throughput screening methods for understanding complex chemical processes and for formulating materials with desirable properties. Despite the rate of advancement in this field, groundbreaking potential of these approaches is yet to be realized. Moreover, there are few or no conferences dedicated to the application of these methods to chemical and material problems. In order to stimulate further improvements in the field, we propose a workshop including researchers involved in development of new algorithms and applications of such methodologies to problems in chemistry and materials.
We wish to ensure an intimate workshop setting, with no more than 20 to 25 participants. If you are interested in attending, but have not received an invitation, please contact the workshop organizer before registering.
TSRC is about expanding the frontiers of science, exploring new ideas, and building collaborations. The workshop schedule will allow for substantial unstructured time for participants to talk and think. All participants are expected to stay for the entire duration of the workshop.
|Alzate-Vargas, Lorena||Los Alamos National Laboratory|
|Bowman, Joel||Emory University|
|Kulik, Heather||Massachusetts Institute of Technology|
|Maurer, Reinhard||University of Warwick|
|Messerly, Richard||Los Alamos National Laboratory|
|Prezhdo, Oleg||University of Southern California|
|Reiher, Markus||ETH Zurich|