Machine learning is no longer restricted to data analysis, currently being used in theory, experiment and simulation - a sign that AI is becoming pervasive in all traditional aspects of research. But are theorists, experimentalists and computational scientists aware of each other’s problems, and the solutions developed to tackle them? Are researchers working in different areas of physics aware of developments in other areas?
About the event
With the bigger and better observatories and state-of-the-art large-scale simulations, researchers in astrophysics and cosmology need to handle and analyse ever-growing volumes of data. These communities have been pioneering new data analysis methods, planning infrastructure to support the huge data-pipelines and building a community approach to tackling their problems. What can the wider physics and AI communities learn from their experience and how can they contribute to the ongoing efforts?
Who should attend?
This event is of interest to physicists from all fields who are using or intending to use AI in their research. It is equally relevant to AI scientists who are developing new machine learning tools and who would want to know what types of problems physicists are trying to solve. The talks and the follow-up discussion will be kept non-technical so that the content is accessible to non-specialists. At the end there will be an opportunity to ask questions.
Chair - Professor Benjamin Joachimi
16:00 - 16:05 - Event introduction
16:05 - 16:25 - 20 minute presentation
16:25 - 16:45 - 20 minute presentation
16:45 - 17:05 - 20 minute Q&A session
17:05 - 17:10 - Event summary
If you have any further questions about the event, please contact Zaynab Ismail (Research Project Manager) at [email protected].