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Dr. David Stracuzzi is a Principal Member of Technical Staff at Sandia National Laboratories and has been studying machine learning and artificial intelligence for 20 years. He currently leads several projects that apply data-driven modeling and uncertainty analysis methods to tasks related to remote sensing data, pattern-of-life data, geophysical data, and data related to physics-based simulations. Prior to joining Sandia in 2010, Dr. Stracuzzi was a member of the research faculty at Arizona State University working on computational cognitive architectures for developing intelligent agents.
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.
Susan Clark has been a scientist at Sandia National Laboratories since 2013 where she has worked on a variety of quantum information-related projects on different platforms, including trapped ions and gate-defined quantum dots in silicon. She is currently the PI of the DOE-funded Quantum Scientific Computing Open User Testbed (QSCOUT) at Sandia, a project which aims to build, maintain, and provide access to quantum hardware based on trapped ions to scientists around the world. Prior to joining Sandia, she did her postdoctoral work at the Joint Quantum Institute at University of Maryland with Chris Monroe. There, she researched quantum networking with trapped ions via photons and robust two-qubit gates via phonons. Prior to her postdoctoral work, she graduated with a PhD and Masters in Applied Physics from Stanford University in 2010. At Stanford, under the direction of Professor Yoshi Yamamoto, she studied and characterized a variety of optical solid-state qubits including electron spins of silicon donors in bulk GaAs and single fluorine donors in ZnSe.
Tuan Ho is a Senior Member of the Technical Staff in the Geochemistry Department at Sandia National Laboratories. He earned his Bachelor of Engineering from Ho Chi Minh City University of Technology, Vietnam and his PhD from University College London, UK. His research interests include molecular interaction/properties in natural/engineering nanoporous materials related to subsurface applications: shale gas production, nuclear waste disposal, carbon dioxide capture and geological storage.
John Fulton is a manager at Sandia National Laboratories where he has worked for the last two decades. During his time at Sandia John led the development of the Turbo FRMAC software and gained expertise in Health Physics, Emergency Response, and the methodologies and operation of the Federal Radiological Management and Assessment Center. John also led the development of the Sandia Hazard Assessment Response Capability (SHARC) where he developed expertise in atmospheric transport and dispersion of radioactive source terms and fallout as well as prompt nuclear effects. John recently led the development of the Launch Safety Atmospheric Transport and Consequence group where he applied his expertise in dynamic plume rise, health physics, atmospheric transport and dispersion to assess the potential impacts of a launch failure for the Mars 2020 launch.