Show Notes
Imagine if your doctor had a digital model of your heart, personalised to you and updated with your latest medical information. This isn't science fiction – this revolutionary healthcare is being tested now. In this podcast we speak to Steven Niederer, who leads the CVDNet project developing and testing these ideas, and his colleague Richard Wilkinson, from the University of Nottingham. Richard is one of the organisers of the long research programme, Representing, calibrating & leveraging prediction uncertainty from statistics to machine learning (RCL), held earlier this year at the Isaac Newton Institute for the Mathematical Sciences (INI). We first spoke to Steven back in 2019 when he helped organise the Fickle Heart programme at the INI. In this podcast, Richard and Steven tell us about digital twins, digital hearts, and how the RCL programme and CVDNet build on the work started back in 2019 with the Fickle Heart programme. You can find out more about some of the ideas discussed in this podcast in these short introductions:
Maths in a Minute: Mathematical models Maths in a Minute: Differential equations Maths in Minute: Machine learning
This content was produced as part of our collaborations with the Isaac Newton Institute for Mathematical Sciences (INI) and the Newton Gateway to Mathematics. The INI is an international research centre and our neighbour here on the University of Cambridge's maths campus. The Newton Gateway is the impact initiative of the INI, which engages with users of mathematics. You can find all the content from the collaboration here.
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In this episode, we meet the CEO of one of the most important institutions in mathematics - arXiV. Around since 1991, the website is a publicly accessible home for mathematical research before it is officially published in journals. Around 1,000 articles are published on arXiv every day — it has hosted everything from the proof of the Poincaré Conjecture to some of the newest research from AI companies like DeepSeek and Gemini. We spoke to Ramin Zabih, a Professor at Cornell Tech and Interim Chief Executive Officer at ArXiv, about the organisation and how it supports the very best of mathematical research. Ramin explains why early access is so important, the site’s role in making maths more robust, and why arXiv can publish things that journals can’t. Particularly importantly, he talks about the impact of AI on arXiv’s work. To learn more:
What is the potential of artificial intelligence (AI) in scientific research? In this episode, Cambridge Professor James Fergusson talks about some cutting-edge research which addresses this question. James is Director of the Infosys-Cambridge AI Centre, an innovative partnership between traditional academia and industry. James showed us how AI is quickly becoming the most effective tool for some kinds of data analysis, and even highlighted successful experiments he ran using AI to write research papers. James is also Executive Director of the University of Cambridge's new Master's programme in Data Intensive Science, which is training up the next leaders in the field. He talked us through the programme’s benefits, the institutional approach to AI and the best ways to advance the field. If you'd like to find out more, you might be interested in:
Welcome to the latest episode of Maths on the Move! In this episode we spoke to Cambridge Professor of Theoretical Physics Ulrich Sperhake and his graduate student, Seppe Staelens, about boson stars: hypothetical objects that might be masquerading as black holes. Our conversation with Ulrich and Seppe marked the tenth anniversary of the first detection of gravitational waves. As Ulrich explained back then, gravitational waves "opened our ears to the Universe in a waveband in which we have been 100% deaf up to now" and they also help us understand black holes and boson stars. In this podcast Seppe and Uli explain more, taking us to the frontiers of current research.. To find out more about the topics discussed in this podcast, you might like: