Category: Uncategorised
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Interview: LML Fellow Emilie Soysal
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Emilie Rosenlund Soysal joined LML as a research fellow in January 2024. Her current research focuses on the economic modelling of climate change and disaster risk, tipping points and extinction. She is particularly interested in optimal policies under the presence of absorbing […]
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Data Science for Social Good — identifying students at risk of missing out on higher education
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Datafest, a recent event at The Shard in London, marked the culmination of a twelve week effort by students participating in the 2023 Data Science for Social Good (DSSG) Summer Fellowship programme at the University of Warwick, supported by the London Mathematical […]
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Data Science for Social Good — helping consumers to identify greenwashing
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Datafest, a recent event at The Shard in London, marked the culmination of a twelve week effort by students participating in the 2023 Data Science for Social Good (DSSG) Summer Fellowship programme at the University of Warwick, supported by the London Mathematical […]
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Fighting deforestation in Brazil: gaining insight through data science
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Datafest, a recent event at The Shard in London, marked the culmination of a 12-week effort by students participating in the 2023 Data Science for Social Good (DSSG) Summer Fellowship programme at the University of Warwick, supported by the London Mathematical Laboratory. […]
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Why insurance exists
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A recent issue of Annals of Actuarial Science features a concise essay by Ole Peters, founder of the London Mathematical Laboratory, discussing the concept of insurance – and explaining why it is surprisingly paradoxical from the viewpoint of mainstream economics. The discussion […]
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2022 Christmas message
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As the end of 2022 approaches, I’m looking back at what’s been going on at LML and can report that we have a few big things to celebrate. In 2022 LML received the most generous gift in its history so far, in […]
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LML Discussions: lessons to learn about modelling from the COVID experience
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Scientists regularly use models, which help make their thinking definite, specific, and easier to challenge, test and refine. Scientists know that models always have shortcomings. There’s no such thing as “modelling the real thing,” only various approximations thereof, which may be more […]