Archive | News

Welcome to Sam Power

The School of Maths welcomes Sam Power as a new Lecturer in the Institute of Statistical Science Dr Power received his PhD degree in 2020 from the Statistical Laboratory at the University of Cambridge, where his thesis focused on the synthesis and analysis of stochastic simulation algorithms for Bayesian inference. He then joined the School […]

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Professor Peter Green elected as Biometrika Trust Chair

Peter Green has been elected Chair of the Biometrika Trust, and took office on 1 December 2023 Biometrika is one of the leading statistics journals in the world, and over the decades its pages have publishedmany of the seminal works of our discipline. It was founded in 1901 by Karl Pearson, Francis Galton and Raphael […]

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New papers shed light on wildcat mystery

New research from the Institute for Statistical Science has shown that wildcats in Britain lived alongside domestic cats since their introduction 2,000 years by the Romans, but only started interbreeding 60 years ago. Dan Lawson worked with Mark Beaumont from Biology and NERC-funded Bristol PhD student Jo Howard-McCombe from the Royal Zoological Society of Scotland […]

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Four papers accepted at NeurIPS

NeurIPS is the world’s premier conference in Machine Learning and Artificial Intelligence. Competition to publish in the peer-reviewed proceedings of NeurIPS is very intense. Over 12,000 papers were submitted to NeurIPS 2023, which will be held in New Orleans in December. Members of the Institute for Statistical Science in the School of Mathematics had another […]

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Earthquake Forecasting Paper published in American Geophysical Union journal: Earth’s Future

COMPASS Student Sam Stockman and Statistics Institute member Dan Lawson have worked collaboratively with seismologist Max Werner from the School of Earth Sciences to publish a paper into the American Geophysical Union journal; Earth’s Future. Titled ‘Forecasting the 2016-2017 Central Apennines Earthquake Sequence with a Neural Point Process’, the paper constructs a temporal point process […]

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Papers on high-dimensional time series modelling accepted into Journal of the American Statistical Association and Journal of Business & Economic Statistics

Dr Haeran Cho and Dom Owens (COMPASS PhD student), in collaboration with Prof Matteo Barigozzi (Bologna), have had a new paper accepted into Journal of Business & Economic Statistics. Titled ‘FNETS: Factor-adjusted network estimation and forecasting for high-dimensional time series’, the paper proposes a new model for high-dimensional time series data exhibiting dominant dependence, a […]

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Pure Mathematics welcomes Dr Alice Pozzi

Dr Pozzi received her PhD degree in 2018 from McGill University in Montreal, under the supervision of Henri Darmon and Payman Kassei. As a postdoctoral researcher, she has worked with Sarah Zerbes at University College London and she held a Chapman Fellowship in Pure Mathematics at Imperial College London. Her research interests cover a broad […]

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Statistics Institute welcomes two new lecturers

The Institute for Statistical Science is very pleased to welcome Dr Juliette (Ettie) Unwin and Dr Katarzyna Reluga, who have both joined as Lecturers in Statistical Science. Dr Unwin’s PhD was in uncertainty quantification in engineering systems using the Multilevel Monte Carlo method at the University of Cambridge.  Then she switched fields to modelling infectious […]

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Prof. Jens Eggers awarded 2023 LMS Naylor Prize

Congratulations to Prof. Jens Eggers, who has been awarded the 2023 London Mathematical Society Naylor Prize. The School of Mathematics is delighted to congratulate Prof. Jens Eggers on his recent award of the Naylor prize from the London Mathematical Society. He has been cited for his profound contributions to the theoretical understanding of singularities, and […]

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Epidemic modelling paper published in JRSS(B)

Current and former Statistics Institute members Michael Whitehouse, Nick Whiteley and Lorenzo Rimella have had a paper related to epidemic modelling accepted in the Journal of the Royal Statistical Society Series B. The paper introduces Poisson Approximate Likelihood (PAL) methods for fitting stochastic compartmental models. Compartmental modelling is one of the most widespread methods for […]

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