Tim Draelos has been at Sandia for over 32 years and received his Ph.D. at UNM in 1998, focusing on constructive neural networks. He has spent the last ten years conducting deep learning R&D, including work on seismic signal detection, phase identification, and event discrimination. He chaired special sessions on Machine Learning in Seismology at the 2016 and 2017 Seismological Society of America annual meetings and 2017 American Geophysical Union fall meeting. He has taught classes on machine and deep learning and was the founder and general chair of the 1st three Sandia Machine Learning and Deep Learning Workshops, starting in 2017. He has published papers in the Bulletin of the Seismological Society of America, Seismological Research Letters, and various machine learning conferences.