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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.
Matthew Marinella is a Principal Member of the Technical Staff with Sandia National Labs. He is Principal Investigator for Sandia’s Nonvolatile Memory Program and leads research projects on neuromorphic, radiation hard, and energy efficient computing. Dr. Marinella chairs the Emerging Memory Devices Section for the IRDS Roadmap Beyond CMOS Chapter, serves on various technical program committees, and is a Senior Member of the IEEE. He received a PhD in electrical engineering from Arizona State University under Dieter K. Schroder in 2008.
Dr. Kiran Lakkaraju is a Senior Member of the Technical Staff at Sandia National Laboratories, California in the Systems Research & Analysis III group. Kiran’s research has been marked by extensive interdisciplinary efforts that bring together the social and computational sciences. Kiran has been investigating how games, including Massively Multiplayer Online Games and wargames can be used as a means to systematically and quantitatively study conflict escalation and global strategic stability. Kiran is a member of the Project on Nuclear Gaming which has developed one of the first experimental wargames, SIGNAL. Kiran has a background in artificial intelligence, multi-agent systems and computational social science. He holds a M.S. and Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign.
Emily Donahue is a member of the technical staff at Sandia. She applies state-of-the-art machine learning innovations to novel applications for national security. She performs research in unsupervised learning, anomaly detection, and data-driven code acceleration. Emily earned her Master of Engineering at Cornell University with a focus in computer vision. While away from her computer, she enjoys landscape painting and rock climbing.
Raga is a member of the technical staff at Sandia. She is a molecular, developmental and, most recently, computational biologist with a background in regulation of gene expression and cell fates in mammalian systems. Her main area of focus is characterizing, monitoring, and engineering of molecular pathways within cells to alter their phenotypic outcomes. She combines the use of bioinformatics, modeling, and machine learning with experimental biology to dissect the mechanisms by which cellular responses can be programmed, both intrinsically and by external influences.
Raga’s current projects include enhancing antimicrobial and immunomodulatory activity of mesenchymal stromal cells through CRISPR-based gene modulation, prediction of CRISPR efficiency across cell types, and generating optogenetic (light-activatable) neurons and neuron-like cells for interfacing with low-power computing devices.
She received her Bachelor of Arts in Natural Sciences (Biochemistry) from the University of Cambridge, UK, in 2004. She then went on to receive her Ph.D. in Biochemistry, Cell and Molecular Biology (laboratory of Dr. W. Lee Kraus) at Cornell University, Ithaca, NY, in 2010.