IDEAL

Image across Domains, Experiments, Algorithms and Learning

Dani Ushizima is a Staff Scientist at CRD-LBNL, a Data Scientist at the BIDS-UCB and an Affiliate Faculty at BCHSI-UCSF. She's a computer scientist, graduated in computer vision from the University of Sao Paulo, where she designed shape analysis and classification algorithms, targeting cell screening. Almost 15 years at LBNL, her research in image analysis and pattern recognition has impacted a broad array of scientific investigations that depends on experimental data, particularly images. In 2016, Ushizima received the U.S. Department of Energy Early Career Research award to focus on pattern recognition applied to diverse scientific domains - images range from biomedical to new materials science samples. She is also the recipient of the Science without Borders Special Researcher award (CNPq/Brazil) for her work on machine learning applied to cytology, as part of a cancer research initiative focused on women's healthcare. She has also led the Computer Vision team for the Center for Advanced Mathematics for Energy Related Applications (CAMERA).

Other initiatives she co-leads are CRIC and ImageXD. Proud to be part of the Machine Learning and Analytics Group. Since the pandemic started, she's been also investigating lung scans for COVID-19 screening .