Towards automated quality assessment and analysis of targeted mass spectrometry data using machine learning Shadi Eshghi Genentech
Shadi Eshghi is a scientist in the biomarker development department at Genentech. Her work focuses on development of bioinformatics tools and techniques to facilitate analysis and interpretation of mass spectrometry, flow cytometry and mass cytometry data. Prior to joining Genentech, Shadi worked in Dr. Hui Zhang’s lab at Johns Hopkins University on novel computational and experimental methods for exploring the glycome and glycoproteome using mass spectrometry. Shadi obtained a Ph.D. in biomedical engineering from Johns Hopkins University and a B.Sc. in electrical engineering and is a 2016 Siebel Scholar.