Faculty Summit 2016 – Computational Problems in Healthcare and Biomedicine

  • Jennifer Listgarten, Nicolo Fusi, Dana Pe'er, Eran Segal | Microsoft, Microsoft, Columbia University, Weizmann Institute of Science

Molecular biology, healthcare and medicine have been slowly morphing into large-scale, data driven sciences dependent on machine learning, natural language processing, applied statistics, privacy and security, compression and efficient search. For example, drug development timelines can be dramatically reduced by modelling the effect of already-approved drugs on large-scale measurements of expression of genes in diseased cells; the progression of cancer and the evolution of stem cells can be tracked using manifold embedding techniques leading to better understanding and more effective treatments; latent variable models deployed on large-scale DNA sequencing of microbial communities pervasive in our bodies and environment are transforming our understanding of health and disease; revolutionary new techniques for gene editing are being made more effective by leveraging machine learning predictive models. In this session, we highlight a few examples that are helping to transform the world and shine a light on where this quickly-moving area is headed.

People

Chair: Jennifer Listgarten, Microsoft Research
Speakers:

Series: Microsoft Research Faculty Summit