Artificial Intelligence - Accelerating Research at the University of Cambridge

Artificial Intelligence - Accelerating Research at the University of Cambridge

Artificial Intelligence - Accelerating Research at the University of Cambridge

event Wednesday 27 November 2024 schedule 6.30pm - 7.30pm GMT
event Wednesday 27 November 2024 schedule 6.30pm - 7.30pm GMT
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This webinar offers an intriguing exploration into how AI is advancing science, and the real-world implications.
Online
Open to: 
Alumni and guests
Friends and supporters
Postgraduate students
Public (open to all)
Undergraduates
University members

Join Dr Cranmer, Dr Lines and Professor Vendruscolo for an insight on how AI is accelerating research in Cambridge.

The webinar will be chaired by Dr James Fergusson, Department of Applied Mathematics and Theoretical Physics.

Speakers

Dr Miles Cranmer (University of Cambridge)

Dr Cranmer

Dr Cranmer works on interpretable machine learning for the physical sciences.

Dr Emily Lines (University of Cambridge)

Dr Lines

Dr Lines' research includes applying modern data science techniques to high-resolution remote sensing data of forests to improve the extraction of ecologically meaningful information.

Professor Michele Vendruscolo (University of Cambridge)

Prof Vendruscolo

Professor Vendruscolo's research is aimed at understanding the molecular origins of neurodegenerative disorders, including Alzheimer's and Parkinson's diseases, and at opening in this way novel opportunities for drug discovery to prevent, delay or treat these conditions.

Dr James Fergusson (University of Cambridge)

Dr Fergusson

Dr Fergusson is a member of the Department of Applied Mathematics and Theoretical Physics GR research group. His current research interests are connecting higher order correlation functions of cosmological data sets with theoretical models of the early universe. James also directs the Centre for Doctoral Training in Data Intensive Science, the MPhil in Data Intensive Science, and the Cambridge Infosys AI hub. 

Booking information