̽��ֱ�� of Cambridge - Department of Pure Mathematics and Mathematical Statistics

New datasets will train AI models to think like scientists

sc604 — Mon, 02 Dec 2024 15:59:08 +0000

̽��ֱ��initiative, called Polymathic AI, uses technology like that powering large language models such as OpenAI’s ChatGPT or Google’s Gemini. But instead of ingesting text, the project’s models learn using scientific datasets from across astrophysics, biology, acoustics, chemistry, fluid dynamics and more, essentially giving the models cross-disciplinary scientific knowledge.

“These datasets are by far the most diverse large-scale collections of high-quality data for machine learning training ever assembled for these fields,” said team member Michael McCabe from the Flatiron Institute in New York City. “Curating these datasets is a critical step in creating multidisciplinary AI models that will enable new discoveries about our universe.”

On 2 December, the Polymathic AI team released two of its open-source training dataset collections to the public — a colossal 115 terabytes, from dozens of sources — for the scientific community to use to train AI models and enable new scientific discoveries. For comparison, GPT-3 used 45 terabytes of uncompressed, unformatted text for training, which ended up being around 0.5 terabytes after filtering.

̽��ֱ��full datasets are available to download for free on HuggingFace, a platform hosting AI models and datasets. ̽��ֱ��Polymathic AI team provides further information about the datasets in two papers accepted for presentation at the NeurIPS machine learning conference, to be held later this month in Vancouver, Canada.

“Just as LLMs such as ChatGPT learn to use common grammatical structure across languages, these new scientific foundation models might reveal deep connections across disciplines that we’ve never noticed before,” said Cambridge team lead Dr Miles Cranmer from Cambridge’s Institute of Astronomy. “We might uncover patterns that no human can see, simply because no one has ever had both this breadth of scientific knowledge and the ability to compress it into a single framework.”

AI tools such as machine learning are increasingly common in scientific research, and were recognised in two of this year’s Nobel Prizes. Still, such tools are typically purpose-built for a specific application and trained using data from that field. ̽��ֱ��Polymathic AI project instead aims to develop models that are truly polymathic, like people whose expert knowledge spans multiple areas. ̽��ֱ��project’s team reflects intellectual diversity, with physicists, astrophysicists, mathematicians, computer scientists and neuroscientists.

̽��ֱ��first of the two new training dataset collections focuses on astrophysics. Dubbed the Multimodal Universe, the dataset contains hundreds of millions of astronomical observations and measurements, such as portraits of galaxies taken by NASA’s James Webb Space Telescope and measurements of our galaxy’s stars made by the European Space Agency’s Gaia spacecraft.

̽��ֱ��other collection — called the Well — comprises over 15 terabytes of data from 16 diverse datasets. These datasets contain numerical simulations of biological systems, fluid dynamics, acoustic scattering, supernova explosions and other complicated processes. Cambridge researchers played a major role in developing both dataset collections, working alongside PolymathicAI and other international collaborators.

While these diverse datasets may seem disconnected at first, they all require the modelling of mathematical equations called partial differential equations. Such equations pop up in problems related to everything from quantum mechanics to embryo development and can be incredibly difficult to solve, even for supercomputers. One of the goals of the Well is to enable AI models to churn out approximate solutions to these equations quickly and accurately.

“By uniting these rich datasets, we can drive advancements in artificial intelligence not only for scientific discovery, but also for addressing similar problems in everyday life,” said Ben Boyd, PhD student in the Institute of Astronomy.

Gathering the data for those datasets posed a challenge, said team member Ruben Ohana from the Flatiron Institute. ̽��ֱ��team collaborated with scientists to gather and create data for the project. “ ̽��ֱ��creators of numerical simulations are sometimes sceptical of machine learning because of all the hype, but they’re curious about it and how it can benefit their research and accelerate scientific discovery,” he said.

̽��ֱ��Polymathic AI team is now using the datasets to train AI models. In the coming months, they will deploy these models on various tasks to see how successful these well-rounded, well-trained AIs are at tackling complex scientific problems.

“It will be exciting to see if the complexity of these datasets can push AI models to go beyond merely recognising patterns, encouraging them to reason and generalise across scientific domains,” said Dr Payel Mukhopadhyay from the Institute of Astronomy. “Such generalisation is essential if we ever want to build AI models that can truly assist in conducting meaningful science.”

“Until now, haven’t had a curated scientific-quality dataset cover such a wide variety of fields,” said Cranmer, who is also a member of Cambridge’s Department of Applied Mathematics and Theoretical Physics. “These datasets are opening the door to true generalist scientific foundation models for the first time. What new scientific principles might we discover? We're about to find out, and that's incredibly exciting.”

̽��ֱ��Polymathic AI project is run by researchers from the Simons Foundation and its Flatiron Institute, New York ̽��ֱ��, the ̽��ֱ�� of Cambridge, Princeton ̽��ֱ��, the French Centre National de la Recherche Scientifique and the Lawrence Berkeley National Laboratory.

Members of the Polymathic AI team from the ̽��ֱ�� of Cambridge include PhD students, postdoctoral researchers and faculty across four departments: the Department of Applied Mathematics and Theoretical Physics, the Department of Pure Mathematics and Mathematical Statistics, the Institute of Astronomy and the Kavli Institute for Cosmology.

What can exploding stars teach us about how blood flows through an artery? Or swimming bacteria about how the ocean’s layers mix? A collaboration of researchers, including from the ̽��ֱ�� of Cambridge, has reached a milestone toward training artificial intelligence models to find and use transferable knowledge between fields to drive scientific discovery.

Alex Meng, Aaron Watters and the Well Collaboration

A mosaic of simulations included in the Well collection of datasets

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Early career researchers win major European funding

ta385 — Thu, 05 Sep 2024 09:30:00 +0000

Of 3,500 proposals reviewed by the ERC, only 14% were selected for funding – Cambridge has the highest number of grants of any UK institution.

ERC Starting Grants – totalling nearly €780 million – support cutting-edge research in a wide range of fields, from life sciences and physics to social sciences and humanities.

̽��ֱ��awards help researchers at the beginning of their careers to launch their own projects, form their teams and pursue their most promising ideas. Starting Grants amount to €1.5 million per grant for a period of five years but additional funds can be made available.

In total, the grants are estimated to create 3,160 jobs for postdoctoral fellows, PhD students and other staff at host institutions.

Cambridge’s recipients work in a wide range of fields including plant sciences, mathematics and medicine. They are among 494 laureates who will be leading projects at universities and research centres in 24 EU Member States and associated countries. This year, the UK has received grants for 50 projects, Germany 98, France 49, and the Netherlands 51.

Cambridge’s grant recipients for 2024 are:

Adrian Baez-Ortega (Dept. of Veterinary Medicine, Wellcome Sanger Institute) for Exploring the mechanisms of long-term tumour evolution and genomic instability in marine transmissible cancers

Claudia Bonfio (MRC Laboratory of Molecular Biology) for Lipid Diversity at the Onset of Life

Tom Gur (Dept. of Computer Science and Technology) for Sublinear Quantum Computation

Leonie Luginbuehl (Dept. of Plant Sciences) for Harnessing mechanisms for plant carbon delivery to symbiotic soil fungi for sustainable food production

Julian Sahasrabudhe (Dept. of Pure Mathematics and Mathematical Statistics) for High Dimensional Probability and Combinatorics

Richard Timms (Cambridge Institute for Therapeutic Immunology and Infectious Disease) for Deciphering the regulatory logic of the ubiquitin system

Hannah Übler (Dept. of Physics) for Active galactic nuclei and Population III stars in early galaxies

Julian Willis (Yusuf Hamied Department of Chemistry) for Studying viral protein-primed DNA replication to develop new gene editing technologies

Federica Gigante (Faculty of History) for Unveiling Networks: Slavery and the European Encounter with Islamic Material Culture (1580– 1700) – Grant hosted by the ̽��ֱ�� of Oxford

Professor Sir John Aston FRS, Pro-Vice-Chancellor for Research at the ̽��ֱ�� of Cambridge, said:

“Many congratulations to the recipients of these awards which reflect the innovation and the vision of these outstanding investigators. We are fortunate to have many exceptional young researchers across a wide range of disciplines here in Cambridge and awards such as these highlight some of the amazing research taking place across the university. I wish this year’s recipients all the very best as they begin their new programmes and can’t wait to see the outcomes of their work.”

Iliana Ivanova, European Commissioner for Innovation, Research, Culture, Education and Youth, said:

“ ̽��ֱ��European Commission is proud to support the curiosity and passion of our early-career talent under our Horizon Europe programme. ̽��ֱ��new ERC Starting Grants winners aim to deepen our understanding of the world. Their creativity is vital to finding solutions to some of the most pressing societal challenges. In this call, I am happy to see one of the highest shares of female grantees to date, a trend that I hope will continue. Congratulations to all!”

President of the European Research Council, Prof. Maria Leptin, said:

“Empowering researchers early on in their careers is at the heart of the mission of the ERC. I am particularly pleased to welcome UK researchers back to the ERC. They have been sorely missed over the past years. With fifty grants awarded to researchers based in the UK, this influx is good for the research community overall.”

Nine Cambridge researchers are among the latest recipients of highly competitive and prestigious European Research Council (ERC) Starting Grants.

Luginbuehl lab

Plant roots interacting with arbuscular mycorrhizal fungi. Image: Luginbuehl lab

Yes

Licence type:

Attribution

Ten Cambridge scientists elected as Fellows of the Royal Society 2024

Anonymous — Thu, 16 May 2024 08:51:02 +0000

̽��ֱ��Royal Society is a self-governing Fellowship of many of the world’s most distinguished scientists drawn from all areas of science, engineering and medicine.

̽��ֱ��Society’s fundamental purpose, as it has been since its foundation in 1660, is to recognise, promote and support excellence in science and to encourage the development and use of science for the benefit of humanity.

This year, over 90 researchers, innovators and communicators from around the world have been elected as Fellows of the Royal Society for their substantial contribution to the advancement of science. Nine of these are from the ̽��ֱ�� of Cambridge.

Sir Adrian Smith, President of the Royal Society said: “I am pleased to welcome such an outstanding group into the Fellowship of the Royal Society.

“This new cohort have already made significant contributions to our understanding of the world around us and continue to push the boundaries of possibility in academic research and industry.

“From visualising the sharp rise in global temperatures since the industrial revolution to leading the response to the Covid-19 pandemic, their diverse range of expertise is furthering human understanding and helping to address some of our greatest challenges. It is an honour to have them join the Fellowship.”

̽��ֱ��Fellows and Foreign Members join the ranks of Stephen Hawking, Isaac Newton, Charles Darwin, Albert Einstein, Lise Meitner, Subrahmanyan Chandrasekhar and Dorothy Hodgkin.

̽��ֱ��new Cambridge fellows are:

Professor Sir John Aston Kt FRS

Aston is the Harding Professor of Statistics in Public Life at the Statistical Laboratory, Department of Pure Mathematics and Mathematical Statistics, where he develops techniques for public policy and improves the use of quantitative methods in public policy debates.

From 2017 to 2020 he was the Chief Scientific Adviser to the Home Office, providing statistical and scientific advice to ministers and officials, and was involved in the UK’s response to the Covid pandemic. He was knighted in 2021 for services to statistics and public policymaking, and is a Fellow of Churchill College.

Professor Sarah-Jayne Blakemore FBA FMedSci FRS

Blakemore is the Professor of Psychology and Cognitive Neuroscience, Department of Psychology, and leader of the Developmental Cognitive Neuroscience Group. Her research focuses on the development of social cognition and decision making in the human adolescent brain, and adolescent mental health.

Blakemore has been awarded several national and international prizes for her research, and is a Fellow of the British Academy, the American Association of Psychological Science and the Academy of Medical Sciences.

Professor Patrick Chinnery FMedSci FRS

Chinnery is Professor of Neurology and head of the ̽��ֱ��’s Department of Clinical Neurosciences, and a Fellow of Gonville & Caius College. He was appointed Executive Chair of the Medical Research Council last year, having previously been MRC Clinical Director since 2019.

His principal research is the role of mitochondria in human disease and developing new treatments for mitochondrial disorders. Chinnery is a Wellcome Principal Research Fellow with a lab based in the MRC Mitochondrial Biology Unit and jointly chairs the NIHR BioResource for Translational Research in Common and Rare Diseases. He is a Fellow of the Academy of Medical Sciences.

Professor Rebecca Fitzgerald OBE FMedSci FRS

Fitzgerald is Professor of Cancer Prevention in the Department of Oncology and the inaugural Director of the ̽��ֱ��’s new Early Cancer Institute, which launched in 2022. She is a Fellow of Trinity College.

Her pioneering work to devise a first-in-class, non-endoscopic capsule sponge test for identifying individuals at high risk for oesophageal cancer has won numerous prizes, including the Westminster Medal, and this test is now being rolled out in the NHS and beyond by her spin-out Cyted Ltd.

Professor David Hodell FRS

Hodell is the Woodwardian Professor of Geology and Director of the Godwin Laboratory for Palaeoclimate Research in the Department of Earth Sciences, and a Fellow of Clare College.

A marine geologist and paleoclimatologist, his research focuses on high-resolution paleoclimate records from marine and lake sediments, as well as mineral deposits, to better understand past climate dynamics. Hodell is a fellow of the American Geophysical Union and the American Association for the Advancement of Science. He has received the Milutin Milankovic Medal.

Professor Eric Lauga FRS

Lauga is Professor of Applied Mathematics in the Department of Applied Mathematics and Theoretical Physics, where his research is in fluid mechanics, biophysics and soft matter. Lauga is the author, or co-author, of over 180 publications and currently serves as Associate Editor for the journal Physical Review Fluids.

He is a recipient of three awards from the American Physical Society: the Andreas Acrivos Dissertation Award in Fluid Dynamics, the François Frenkiel Award for Fluid Mechanics and the Early Career Award for Soft Matter Research. He is a Fellow of the American Physical Society and of Trinity College.

Professor George Malliaras FRS

Malliaras is the Prince Philip Professor of Technology in the Department of Engineering, where he leads a group that works on the development and translation of implantable and wearable devices that interface with electrically active tissues, with applications in neurological disorders and brain cancer.

Research conducted by Malliaras has received awards from the European Academy of Sciences, the New York Academy of Sciences, and the US National Science Foundation among others. He is a Fellow of the Materials Research Society and of the Royal Society of Chemistry.

Professor Lloyd Peck FRI FRSB FRS

Peck is a marine biologist at the British Antarctic Survey and a fellow at Wolfson College, Cambridge.

He identified oxygen as a factor in polar gigantism and identified problems with protein synthesis as the cause of slow development and growth in polar marine species. He was awareded a Polar Medal in 2009, the PLYMSEF Silver medal in 2015 and an Erskine Fellowship at the ̽��ֱ�� of Canterbury, Christchurch in 2016-2017.

Professor Oscar Randal-Williams FRS

Randal-Williams is the Sadleirian Professor of Pure Mathematics in the Department of Pure Mathematics and Mathematical Statistics.

He has received the Whitehead Prize from the London Mathematical Society, a Philip Leverhulme Prize, the Oberwolfach Prize, the Dannie Heineman Prize of the Göttingen Academy of Sciences and Humanities, and was jointly awarded the Clay Research Award.

Randal-Williams is one of two managing editors of the Proceedings of the London Mathematical Society, and an editor of the Journal of Topology.

Professor Mihaela van der Schaar FRS

Van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine in the Departments of Applied Mathematics and Theoretical Physics, Engineering and Medicine.

She is the founder and director of the Cambridge Centre for AI in Medicine, and a Fellow at ̽��ֱ��Alan Turing Institute. Her work has received numerous awards, including the Oon Prize on Preventative Medicine, a National Science Foundation CAREER Award, and the IEEE Darlington Award.

Van der Schaar is credited as inventor on 35 US patents, and has made over 45 contributions to international standards for which she received three ISO Awards. In 2019, a Nesta report declared her the most-cited female AI researcher in the UK.

Ten outstanding Cambridge researchers have been elected as Fellows of the Royal Society, the UK’s national academy of sciences and the oldest science academy in continuous existence.

Royal Society

̽��ֱ��Royal Society in central London

Yes

Four Cambridge researchers awarded European Research Council Advanced Grants

jg533 — Fri, 31 Mar 2023 09:43:20 +0000

̽��ֱ��European Research Council (ERC) has announced the award of 218 Advanced Grants to outstanding research leaders across Europe, as part of the Horizon Europe programme.

̽��ֱ��grants, totalling €544 million, support cutting-edge research in a wide range of fields from medicine and physics to social sciences and humanities.

̽��ֱ��ERC is the premier European funding organisation for excellent frontier research. ̽��ֱ��ERC Advanced Grant funding is amongst the most prestigious and competitive EU funding schemes, providing researchers with the opportunity to pursue ambitious, curiosity-driven projects that could lead to major scientific breakthroughs. Grants are awarded to established, leading researchers with a proven track record of significant research achievements over the past decade.

̽��ֱ�� ̽��ֱ�� of Cambridge’s grant awardees are:

Anna Korhonen, Professor of Natural Language Processing in the Faculty of Modern and Medieval Languages and Linguistics, for her project Towards Globally Equitable Language Technologies.

Richard Nickl, Professor of Mathematical Statistics in the Department of Pure Mathematics and Mathematical Statistics, for his project Statistical aspects of non-linear inverse problems.

Peter Sewell, Professor of Computer Science at the Computer Laboratory, for his project Secure Foundations: Verified Systems Software Above Full-Scale Integrated Semantics.

Sujit Sivasundaram, Professor of World History at the Faculty of History, for his project Colombo: Layered Histories in the Global South City.

'Many many congratulations to Anna, Richard, Peter and Sujit on their success. It is fantastic to see the highly innovative work of our researchers being recognised in international competition in this way. We are once again reminded of the commitment of the ERC to cutting edge research across all disciplines and we continue to urge government to swiftly secure association to Horizon Europe,' said Professor Anne Ferguson-Smith, Pro-Vice Chancellor for Research at the ̽��ֱ�� of Cambridge.

"This funding puts our 218 research leaders, together with their teams of postdoctoral fellows, PhD students and research staff, in pole position to push back the boundaries of our knowledge, break new ground and build foundations for future growth and prosperity in Europe,” said Mariya Gabriel, European Commissioner for Innovation, Research, Culture, Education and Youth.

"These new ERC Advanced Grantees are a testament to the outstanding quality of research carried out across Europe. I am especially pleased to see such a high number of female researchers in this competition and that they are increasingly successful in securing funding. We look forward to seeing the results of the new projects in the years to come, with many likely to lead to breakthroughs and new advances,” said Maria Leptin, ERC President.

̽��ֱ��laureates of this grant competition will carry out their projects at universities and research centres in 20 countries in Europe, with the highest number of projects in Germany (37), the UK (35), France (32) and Spain (16). ̽��ֱ��winners come from all over the world, with 27 nationalities represented, notably Germans (36 researchers), French (32), Italians (21), British (19).

This call for proposals attracted nearly 1,650 applications, which were reviewed by panels of renowned researchers. ̽��ֱ��overall success rate was 13.2%. Female researchers account for 23% of all applications, their highest participation rate in Advanced Grant calls up to now.

In addition to strengthening Europe's knowledge base, the grants are expected to create more than 2,000 jobs for postdoctoral fellows, PhD students, and other staff at the host institutions. Past recipients have included Nobel laureates and other leading scientists who have gone on to make major contributions to their respective fields..

Adapted from a press release by the ERC.

̽��ֱ��funding will enable these researchers to explore their most innovative and ambitious ideas.

It is fantastic to see the highly innovative work of our researchers being recognised in international competition in this way.

Anne Ferguson-Smith

yangwenshuang on Getty

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Licence type:

Attribution-Noncommerical

Cambridge academics win European Research Council Advanced Grants

cg605 — Tue, 26 Apr 2022 11:14:19 +0000

Nine Cambridge academics have won Advanced Grants awarded by the European Research Council (ERC). This is the greatest number of grants won by a UK institution in the 2021 round of funding.

Interactive tool helps you decide how to protect yourself and others from COVID-19

sc604 — Thu, 02 Dec 2021 00:08:47 +0000

A new interactive graphic developed by UK researchers and published by ̽��ֱ��BMJ will help people decide what to do in everyday situations to protect themselves, and others, from COVID-19.

Based on estimates provided by 26 international experts, it shows the different pathways that may be taken by the virus that causes COVID-19 when it transfers between two people.

It is designed to help illustrate the risks of catching COVID-19 in different scenarios - and what can be done to reduce those risks - based on the available evidence.

As well as the areas of scientific consensus, it also conveys the uncertainties and the disagreement that exists between experts about how the virus behaves, how it is transmitted, and how we can best reduce the likelihood of transmission through personal and social measures.

̽��ֱ��researchers say the tool should support decision-makers and the public to make informed decisions about how to reduce virus transmission in different contexts, such as how to make a workplace or a public area as safe as it can be while still being open and functional.

To create the tool, the researchers, led by the ̽��ֱ�� of Cambridge, consulted 26 experts from a range of disciplines and countries, asking them for every value needed to underpin the graphic.

These included the importance of different virus transmission routes (eg. small and large airborne droplets, contact with contaminated surfaces) during a range of activities (eg. talking, coughing, exercising, eating) in different environments (eg. outdoors or indoors in different sized rooms, with or without ventilation).

They also gathered estimates on the importance of different protective measures, such as face coverings and screens, physical distancing, hand hygiene, surface cleaning, in reducing transmission.

Analysis of all the values showed that airborne transmission routes were most important in almost all situations, while face coverings, especially when worn by an infected person as a form of source control, were the most important mitigation measure.

But importantly, all routes were considered to play a part in transmission, and simple measures such as physical distancing, hand washing, and respiratory hygiene all made a useful contribution.

̽��ֱ��researchers found important evidence gaps and differences in opinion among experts around several variables, including the role of aerosol transmission; the effects of different kinds of masks on inhaled aerosols; and the effects of face coverings on transfer from hand to eyes, nose, and mouth.

“Everyone has been keen to know how much difference each possible action we’ve been told about makes, and finally we have been able to gather together enough knowledge from experts from around the world and in a range of fields to answer those questions,” said co-lead author Dr Alexandra Freeman from Cambridge’s Winton Centre for Risk & Evidence Communication.

She added: “ ̽��ֱ��tool is interactive, so that you can explore the scenarios that are most relevant to you, whether it’s because you sing in a choir, or want to know about the risks of eating in a small restaurant. How much difference would it make if you opened the windows, or cleaned the surfaces? Have a look and find out.”

“It is all too easy to focus on just a single route of spread for COVID and forget about all the others,” said co-author Harry Rutter from the ̽��ֱ�� of Bath. “One of the ways a tool like this can help is by making it clear that all the transmission routes matter, in different proportions in different contexts. ̽��ֱ��fact that one of those routes - airborne transmission - is the main one in most situations doesn’t mean that we can ignore the others.”

̽��ֱ��authors acknowledge some study limitations and say generating robust evidence on the complex and highly contingent routes of COVID-19 virus transmission is not straightforward. But they say they hope their approach will prove helpful to those faced with the challenge of communicating complex, imprecise, and uncertain evidence in the future.

̽��ֱ��research was supported by the PROTECT COVID-19 National Core Study on transmission and environment (managed by the Health and Safety Executive on behalf of HM Government), and the David and Claudia Harding Foundation. Cambridge co-authors on the paper also included Dr Shaun Fitzgerald from the Department of Engineering and Professor David Spiegelhalter from the Winton Centre for Risk and Evidence Communication.

Reference:
Alexandra LJ Freeman et al. ‘Expert elicitation on the relative importance of possible SARS-CoV-2 transmission routes and the effectiveness of mitigations.’ BMJ Open (2021). DOI: 10.1136/ bmjopen-2021-050869

Harry Rutter et al. ‘Visualising SARS-CoV-2 transmission routes and mitigations.’ BMJ (2021). DOI: 10.1136/bmj-2021-065312

Adapted from a BMJ press release.

Is it risky to sing in a choir? What are the risks of eating in a small restaurant? How much difference does it make to open windows or clean surfaces? New interactive tool helps people make decisions on COVID-19.

Everyone has been keen to know how much difference each possible action we’ve been told about makes, and finally we have been able to gather together enough knowledge from experts from around the world and in a range of fields to answer those questions

Alexandra Freeman

Will Stahl-Timmins, ̽��ֱ��BMJ

COVID-19 risk calculator

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Four Cambridge researchers recognised in the 2022 Breakthrough Prizes

sc604 — Thu, 09 Sep 2021 11:59:47 +0000

Professors Shankar Balasubramanian and David Klenerman, from Cambridge’s Yusuf Hamied Department of Chemistry, have been awarded the 2022 Breakthrough Prize in Life Sciences – the world’s largest science prize – for the development of next-generation DNA sequencing. They share the award with Pascal Mayer, from the French company Alphanosos.

In addition, Professor Suchitra Sebastian, from the Cavendish Laboratory, and Professor Jack Thorne, from the Department of Pure Mathematics and Mathematical Statistics, have been recognised with the New Horizons Prize, awarded to outstanding early-career researchers.

Professor Suchitra Sebastian has been awarded the 2022 New Horizons in Physics Prize for high precision electronic and magnetic measurements that have profoundly changed our understanding of high temperature superconductors and unconventional insulators.

Professor Jack Thorne has been awarded the 2022 New Horizons in Mathematics Prize, for transformative contributions to diverse areas of algebraic number theory, and in particular for the proof, in collaboration with James Newton, of the automorphy of all symmetric powers of a holomorphic modular newform.

Professors Balasubramanian and Klenerman co-invented Solexa-Illumina Next Generation DNA Sequencing (NGS), technology that has enhanced our basic understanding of life, converting biosciences into ‘big science’ by enabling fast, accurate, low-cost and large-scale genome sequencing – the process of determining the complete DNA sequence of an organism’s make-up. They co-founded the company Solexa to make the technology available to the world.

̽��ֱ��benefits to society of rapid genome sequencing are huge. ̽��ֱ��almost immediate identification and characterisation of the virus which causes COVID-19, rapid development of vaccines, and real-time monitoring of new genetic variants would have been impossible without the technique Balasubramanian and Klenerman developed.

̽��ֱ��technology has had – and continues to have – a transformative impact in the fields of genomics, medicine and biology. One measure of the scale of change is that it has allowed a million-fold improvement in speed and cost when compared to the first sequencing of the human genome. In 2000, sequencing of one human genome took over 10 years and cost more than a billion dollars: today, the human genome can be sequenced in a single day at a cost of less than $1,000. More than a million human genomes are sequenced at scale each year, thanks to the technology co-invented by Professors Balasubramanian and Klenerman, meaning we can understand diseases much better and much more quickly. Earlier this year, they were awarded the Millennium Technology Prize. Balasubramanian is also based at the Cancer Research UK Cambridge Institute, and is a Fellow of Trinity College. Klenerman is a Fellow of Christ's College.

Professor Sebastian’s research seeks to discover exotic quantum phases of matter in complex materials. Her group’s experiments involve tuning the co-operative behaviour of electrons within these materials by subjecting them to extreme conditions including low temperature, high applied pressure, and intense magnetic field.

Under these conditions, her group can take materials that are quite close to behaving like a superconductor – perfect, lossless conductors of electricity – and ‘nudge’ them, transforming their behaviour.

“I like to call it quantum alchemy – like turning soot into gold,” Sebastian said. “You can start with a material that doesn’t even conduct electricity, squeeze it under pressure, and discover that it transforms into a superconductor. Going forward, we may also discover new quantum phases of matter that we haven’t even imagined.”

In addition to her physics research, Sebastian is also involved in theatre and the arts. She is Director of the Cavendish Arts-Science Project, which she founded in 2016. ̽��ֱ��programme has been conceived to question and explore material and immaterial universes through a dialogue between the arts and sciences.

“Being awarded the New Horizons Prize is incredibly encouraging, uplifting and joyous,” said Sebastian. “It recognises a discovery made by our team of electrons doing what they're not supposed to do. It's gone from the moment of elation and disbelief at the discovery, and then trying to follow it through, when no one else quite thinks it’s possible or that it could be happening. It’s been an incredible journey, and having it recognised in this way is incredibly rewarding.”

Professor Jack Thorne is a number theorist in the Department of Pure Mathematics and Mathematical Statistics. One of the most significant open problems in mathematics is the Riemann Hypothesis, which concerns Riemann’s zeta function. Today we know that the zeta function is intimately tied up with questions concerning the statistical distribution of prime numbers, such as how many prime numbers there are, how closely they can be found on the number line. A famous episode in the history of the Riemann Hypothesis is Freeman Dyson’s observation that the zeroes of the zeta function appear to obey statistical laws arising from the theory of random matrices, which had first been studied in theoretical physics.

In 1916, during his time in Cambridge, Ramanujan wrote down an analogue of the Riemann zeta function, inspired by his work on the number of ways of expressing a given number as a sum of squares (a problem with a rich classical history), and made some conjectures as to its properties, which have turned out to be related to many of the most exciting developments in number theory in the last century. Actually, there are a whole family of zeta functions, the properties of which control the statistics of the sums of squares problem. Thorne's work, recognised in the prize citation, essentially shows for Ramanujan’s zeta functions what Riemann proved for his zeta function in 1859.

Taking a broader view, Ramanujan’s zeta functions are now seen to fit into the framework of the Langlands Program. This is a series of conjectures, made by Langlands in the 1960’s, which have been described as a “grand unified theory of mathematics”, and which can be used to explain any number of phenomena in number theory. Another famous example is Wiles proof, in 1994, of Fermat’s Last Theorem. Nowadays the essential piece of Wiles’ work is seen as progress towards a small part of the Langlands program. Thorne's work establishes part of Langlands’ conjectures for a class of objects including Ramanujan’s Delta function.

"I am deeply honoured to be awarded the New Horizons Prize for my work in number theory," said Thorne. "Number theory is a subject with a rich history in Cambridge and I feel very fortunate to be able to make my own contribution to this tradition."

For the tenth year, the Breakthrough Prize recognises the world’s top scientists. Each prize is US $3 million and presented in the fields of Life Sciences, Fundamental Physics (one per year) and Mathematics (one per year). In addition, up to three New Horizons in Physics Prizes, up to three New Horizons in Mathematics Prizes and up to three Maryam Mirzakhani New Frontiers Prizes are given out to early-career researchers each year, each worth US $100,000. ̽��ֱ��Breakthrough Prizes were founded by Sergey Brin, Priscilla Chan and Mark Zuckerberg, Yuri and Julia Milner, and Anne Wojcicki.

Four ̽��ֱ�� of Cambridge researchers – Professors Shankar Balasubramanian, David Klenerman, Suchitra Sebastian and Jack Thorne – have been recognised by the Breakthrough Prize Foundation for their outstanding scientific achievements.

L-R: Millennium Technology Prize, Nick Saffell, Jack Thorne

L-R: David Klenerman, Shankar Balasubramanian, Suchitra Sebastian, Jack Thorne

Yes

How accurate were early expert predictions on COVID-19, and how did they compare to the public?

sc604 — Wed, 05 May 2021 18:00:00 +0000

Researchers from the Winton Centre for Risk and Evidence Communication surveyed 140 UK experts and 2,086 UK laypersons in April 2020 and asked them to make four quantitative predictions about the impact of COVID-19 by the end of 2020. Participants were also asked to indicate confidence in their predictions by providing upper and lower bounds of where they were 75% sure that the true answer would fall - for example, a participant would say they were 75% sure that the total number of infections would be between 300,000 and 800,000.

̽��ֱ��results, published in the journal PLOS ONE, demonstrate the difficulty in predicting the course of the pandemic, especially in its early days. While only 44% of predictions from the expert group fell within their own 75% confidence ranges, the non-expert group fared far worse, with only 12% of predictions falling within their ranges. Even when the non-expert group was restricted to those with high numeracy scores, only 16% of predictions fell within the ranges of values that they were 75% sure would contain the true outcomes.

“Experts perhaps didn’t predict as accurately as we hoped they might, but the fact that they were far more accurate than the non-expert group reminds us that they have expertise that’s worth listening to,” said Dr Gabriel Recchia from the Winton Centre for Risk and Evidence Communication, the paper’s lead author. “Predicting the course of a brand-new disease like COVID-19 just a few months after it had first been identified is incredibly difficult, but the important thing is for experts to be able to acknowledge uncertainty and adapt their predictions as more data become available.”

Throughout the COVID-19 pandemic, social and traditional media have disseminated predictions from experts and non-experts about its expected magnitude.

Expert opinion is undoubtedly important in informing and advising those making individual and policy-level decisions. However, as the quality of expert intuition can vary drastically depending on the field of expertise and the type of judgment required, it is important to conduct domain-specific research to establish how good expert predictions really are, particularly in cases where they have the potential to shape public opinion or government policy.

“People mean different things by ‘expert’: these are not necessarily people working on COVID-19 or developing the models to inform the response,” said Recchia. “Many of the people approached to provide comment or make predictions have relevant expertise, but not necessarily the most relevant.” He noted that in the early COVID-19 pandemic, clinicians, epidemiologists, statisticians, and other individuals seen as experts by the media and the general public, were frequently asked to give off-the-cuff answers to questions about how bad the pandemic might get. “We wanted to test how accurate some of these predictions from people with this kind of expertise were, and importantly, see how they compared to the public.”

For the survey, participants were asked to predict how many people living in their country would have died and would have been infected by the end of 2020; they were also asked to predict infection fatality rates both for their country and worldwide.

Both the expert group and the non-expert group underestimated the total number of deaths and infections in the UK. ̽��ֱ��official UK death toll at 31 December was 75,346. ̽��ֱ��median prediction of the expert group was 30,000, while the median prediction for the non-expert group was 25,000.

For infection fatality rates, the median expert prediction was that 10 out of every 1,000 people with the virus worldwide would die from it, and 9.5 out of 1,000 people with the virus in the UK would die from it. ̽��ֱ��median non-expert response to the same questions was 50 out of 1,000 and 40 out of 1,000. ̽��ֱ��real infection fatality rate at the end of 2020—as best the researchers could determine, given the fact that the true number of infections remains difficult to estimate—was closer to 4.55 out of 1,000 worldwide and 11.8 out of 1,000 in the UK.

“There’s a temptation to look at any results that says experts are less accurate than we might hope and say we shouldn’t listen to them, but the fact that non-experts did so much worse shows that it remains important to listen to experts, as long as we keep in mind that what happens in the real world can surprise you,” said Recchia.

̽��ֱ��researchers caution that it is important to differentiate between research evaluating the forecasts of ‘experts’—individuals holding occupations or roles in subject-relevant fields, such as epidemiologists and statisticians—and research evaluating specific epidemiological models, although expert forecasts may well be informed by epidemiological models. Many COVID-19 models have been found to be reasonably accurate over the short term, but get less accurate as they try to predict outcomes further into the future.

Reference:
Gabriel Recchia, Alexandra L.J. Freeman, David Spiegelhalter. ‘How well did experts and laypeople forecast the size of the COVID-19 pandemic?’ PLOS ONE (2021). DOI: 10.1371/journal.pone.0250935

Who made more accurate predictions about the course of the COVID-19 pandemic – experts or the public? A study from the ̽��ֱ�� of Cambridge has found that experts such as epidemiologists and statisticians made far more accurate predictions than the public, but both groups substantially underestimated the true extent of the pandemic.

Predicting the course of a brand-new disease like COVID-19 just a few months after it had first been identified is incredibly difficult, but the important thing is for experts to be able to acknowledge uncertainty and adapt their predictions as more data become available.

Gabriel Recchia

NIH Image Gallery

Novel Coronavirus SARS-Cov-2

Yes

Licence type:

Public Domain