Joint MRC IEU/ICEP Seminar: Mihaela van der Schaar, Professor of Quantitative Finance, Oxford University

16 October 2017, 1.00 PM - 16 October 2017, 2.00 PM



 Monday, 16th October, 2017
13.00 - 14.00 - Room OS6 – Oakfield House

 Mihaela van der Schaar
Professor of Quantitative Finance
xford University

 “Using Machine Learning to Transform Medical Practice and Discovery”



This talk will present my research, which aims to transform medicine through the development and application of dedicated, novel machine learning formalisms, theories, methods, algorithms and systems. Machine learning has transformed many domains from robotics to finance to image recognition, but the transformation of medicine requires an entirely different approach including intimate involvement with the actual medical data and practice – an involvement that has been sorely lacking in much previous work. The overarching goal of my research is to develop novel machine learning theories, methods and systems that are dedicated and uniquely crafted to enable personalized risk prediction, screening, diagnosis, prognosis and treatment so that clinicians can make the best choices for the particular patient at hand. In this talk, I will highlight our research using a few examples from personalized risk prediction and individualized treatment effects.


Mihaela van der Schaar is Man Professor of Quantitative Finance in the Oxford – Man Institute of Quantitative Finance (OMI) and the Department of Engineering Science at Oxford, Fellow of Christ Church College and Faculty Fellow of the Alan Turing Institute [Link], London .

Mihaela's research interests and expertise are in machine learning, data science and decisions for a better planet. In particular, she is interested in developing machine learning and decision theory for finance, medicine and personalized education. She also has research interests and expertise in game theory and applications, and in social, economic and biological networks. She leads the Data Science and Decisions Research Group.





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