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.