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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.
Dr. Warren L. Davis IV is a Principal Member of Technical Staff in the Scalable Analysis and Visualization department in the Center for Computing Research at Sandia National Laboratories. He was the principal investigator for the Hybrid Methods for Cybersecurity Analysis LDRD and the Machine Learning in Adversarial Environments LDRD research projects which had significant impact on cyber operations at the lab. In addition, he is the principal investigator of the Machine Learning for Intelligent Data Capture on Exascale Platforms research project for the DOE ASCR program.
Warren joined the technical staff at Sandia in 2009. He received his Ph.D. in computer science from Florida State in 2006, gaining industry experience as a graduate intern at both the National Astronomical Observatory of Japan in Tokyo and the IBM Almaden Research Center, where he was hired as a Research Staff Member after graduation. Warren has published over 20 journal articles, conference publications, and peer-reviewed presentations, and has worked in the fields of cybersecurity, healthcare informatics, climate modeling, material science, text analytics, combustion, and fluid dynamics, to name a few. In addition, he was awarded the 2019 Black Engineer of the Year Award in Research Leadership.
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.
Lawrence Berkeley National Laboratory (Berkeley Lab), a U. S. Department of Energy Office of Science national lab managed by the University of California, delivers science solutions to the world â solutions derived from hundreds of patented and patent pending technologies plus scores of copyrighted software tools and published, peer-reviewed manuscripts.
Berkeley Lab has more than one hundred cutting-edge research projects using AI to find new scientific solutions to national problems. Through this effort, computer scientists, mathematicians, and domain scientists are collaborating to turn burgeoning datasets into scientific insights. Visit Berkeley Labâs Machine Learning for Science site for more information.
Berkeley Labâs advanced materials expertise is applied to innovation in batteries and other energy storage technologies, semiconductors, and photovoltaics. Additional energy-related areas of expertise include grid modernization and security, bio-based fuels and chemicals and building energy and demand response. Several National User Facilities are available for collaborative engagement: the Advanced Light Source, Molecular Foundry, National Energy Research Scientific Computing Center (NERSC), Energy Sciences Network, and the Joint Genome Institute. Other specialized facilities include FLEXLAB for building energy research and the Advanced Biofuels Process Demonstration Unit.
Ernest Orlando Lawrence, the lab's founder, believed team science yielded the greatest discoveries. That belief is reflected today in interdisciplinary teams and collaborative projects connecting Berkeley Lab, industry, and other research organizations. Berkeley Lab's Intellectual Property Office, connects industry partners with lab innovations and unique facilities to enable lab-to-market transition.
- Basic science: seeks to understand how nature works. This research includes experimental and theoretical work in materials science, physics, chemistry, biology, high-energy physics, and mathematics and computer science, including high performance computing.
- Applied science and engineering helps to find practical solutions to society’s problems. These programs focus primarily on energy resources, environmental management and national security.