Lab Partnering Service Discovery
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Dani Ushizima PhD, is a Staff Scientist at Lawrence Berkeley National Laboratory, a Data Scientist at UC Berkeley and an Affiliate Faculty at UC San Francisco. More than a decade at LBNL, her research in image analysis and pattern recognition has impacted a broad array of scientific investigation that depends on experimental data, particularly images. In 2015, Ushizima received the U.S. Department of Energy Early Career award to focus on pattern recognition applied to diverse scientific domains, such as structural analysis of materials science samples. She is also recipient of the Science without Borders Researcher award (CNPq/Brazil) for her work on machine learning applied to cytology, as part of an initiative focused on public healthcare. She has also led the Image Processing team for the Center for Advanced Mathematics for Energy Related Applications (CAMERA). Recently, she's been investigating lung scans for COVID-19 screening as part of initiatives related to the National Virtual Biotechnology Laboratory (NVBL).
COVID-19-related research: "Can CT Scans Be Used to Quickly and Accurately Diagnose COVID-19?"
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.
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.