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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?"