University of Cambridge > Talks.cam > ML@CL Seminar Series > Probabilistic machine learning methods for uncertainty quantification and decision-making

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Probabilistic machine learning methods for uncertainty quantification and decision-making

Download to your calendar using vCal

If you have a question about this talk, please contact .

My research focuses on the development of probabilistic machine learning methods for uncertainty quantification and data-efficient sequential decision making. I work on the challenges arising when uncertainty of different types (the loss of precision induced by numerical calculations, data errors, model miss-calibration, etc.) need to be be propagated, controlled and reduced in complex pipelines. I am also interested on how causal inference can be used to leverage decision making methods and to improve the understanding of complex systems and processes. As fields of application of my research I am interested in computational biology, health and environmental sciences.

This talk is part of the ML@CL Seminar Series series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

LCHES seminar room, The Leverhulme Centre, The Henry Wellcome Building Old Kitchens, Queens' College (tbc) Morison Room, University Library

Other talks

Cooperation in Nature Tea and Coffee Break Illegal trade in the North Atlantic Title to be confirmed Title TBC Using Light for Cancer Detection
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity