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
Past event
Past event
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.
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.

Artificial Intelligence — Accelerating Research at the University of Cambridge

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.

Professor James Fergusson (Churchill 2004)

Dr Fergusson

Professor James Fergusson is a theoretical cosmologist and award-winning university lecturer at the Department of Applied Mathematics and Theoretical Physics. He is the Executive Director of the Data Intensive Science programmes at the University of Cambridge, and Director of the Infosys Cambridge Enterprise AI Centre.

His research group operates at the interface of physics and artificial intelligence, focusing on areas where AI has the potential to fundamentally transform the way science is conducted. Key research themes include AI for simulations, using physics to deepen our understanding of AI, employing AI to explore equations, advancing AI interpretability and error quantification, and developing agentic automation for scientific discovery.

James frequently delivers talks and workshops on the application of AI in science and business, delivers lectures on the impact of AI via the Judge business school, and his work has been featured in the Financial Times.

Booking information

Booking for this event is now closed.

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