Harshita Sharma

Harshita Sharma is a Senior ML Researcher in Health Intelligence, Microsoft Research Cambridge (UK). She works in the Medical Imaging team, where she explores machine learning solutions aimed towards improving patient outcomes and clinical workflows. Harshita’s research interests include machine learning, image analysis, computer vision, and multimodal clinical data analysis for healthcare. Until June 2021, Harshita worked as a PostDoc in the Department of Engineering Science at the University of Oxford (UK) and was a member of the Biomedical Image Analysis (BioMedIA) group. She worked in the interdisciplinary ERC Project PULSE with the aim to develop multi-modal analysis methods to model sonographic experience and make obstetric ultrasound imaging easier for non-specialists.

In 2010, Harshita obtained her Bachelors degree in electronics and communication engineering from the Indira Gandhi Delhi Technical University of Women (India), and in 2012, her Masters degree in electrical engineering from the Indian Institute of Technology Roorkee. In 2017, Harshita obtained her Ph.D. (Dr.-Ing.) in Computer Vision from Technische Universität Berlin (Germany). She was a member of the Computer Vision and Remote Sensing group (CVRS) at TU Berlin. Harshita also collaborated with Charité University Hospital (Germany), VMScope GmbH Berlin (Germany), and University Hospital Schleswig-Holstein (Germany) to analyse histopathological whole slide images of gastric carcinoma to develop methods in computational pathology for automatic cancer grade classification, necrosis detection and cell nuclei classification.