Machine Intelligence. Working at Microsoft Research Cambridge Here at Microsoft Research in Cambridge, we truly aspire to transform the world through deep research.
Play the video. Work with us. See more career opportunities. Highlighted projects. InnerEye Read more about InnerEye. Enterprise Knowledge Read more about Enterprise Knowledge. See more projects. Meet our research community. Managing patient flows along healthcare pathways is a critical concern for hospitals in both operational and clinical terms. Working with key clinical partners, we are developing Machine-Learning based systems that will offer intelligent insights about these operational and clinical events.
The research adopts a human centred machine learning perspective that combines deep clinical knowledge, ethnographic understanding of clinical work practices and machine learning expertise to develop ML insights that are actionable in real world clinical contexts. The adaptive immune system is an incredibly complex and powerful defense against disease. With Microsoft Immunomics we are developing state-of-the-art deep generative models trained on vast amounts of T-cell repertoire data, learning not only to predict but to understand disease.
By decoding the immune system in this way, we can transform precision diagnostics and treatment options for many diseases. In Project InnerEye , we are developing ML-based productivity tools for the automatic, quantitative analysis of radiological images — in particular, our work turns radiological images into measuring devices. Our focus is on the following applications: 1. COVID has mobilized communities around the world to work together on a range of critical issues required to understand and respond to the current pandemic.
Scientific research is vital to both this near and long-term pandemic preparedness. Follow us:. Share this page:.
We are particularly interested in the following areas: Hospital care Managing patient flows along healthcare pathways is a critical concern for hospitals in both operational and clinical terms. Share this page:. Overview Selected Publications Collaborators Projects We encompass several approaches to computational biology: we try to frame the biological question under consideration in terms of more standard problems in computer science, like clustering, Steiner trees, flow problems, etc.
People People. Learn more. Sharon Gillett Technical Advisor and Sr.
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