̽��ֱ�� of Cambridge - Selwyn College

10 Cambridge AI spinouts

skbf2 — Wed, 02 Apr 2025 15:20:09 +0000

Meet 10 Cambridge spinouts, all hoping to harness the potential of AI for the good of the planet and its people.

̽��ֱ��Cambridge Awards 2024 for Research Impact and Engagement

zs332 — Mon, 03 Feb 2025 10:27:01 +0000

Meet the winner of the Cambridge Awards 2024 for Research Impact and Engagement and learn more about their projects.

Wrong trees in the wrong place can make cities hotter at night, study reveals

ta385 — Tue, 10 Dec 2024 09:45:00 +0000

Temperatures in cities are rising across the globe and urban heat stress is already a major problem causing illness, death, a surge in energy use to cool buildings down, heat-related social inequality issues and problems with urban infrastructure.

Some cities have already started implementing mitigation strategies, with tree planting prominent among them. But a ̽��ֱ�� of Cambridge-led study now warns that planting the wrong species or the wrong combination of trees in suboptimal locations or arrangements can limit their benefits.

̽��ֱ��study, published today in Communications Earth & Environment found that urban trees can lower pedestrian-level air temperature by up to 12°C. Its authors found that the introduction of trees reduced peak monthly temperatures to below 26°C in 83% of the cities studied, meeting the ‘thermal comfort threshold’. However, they also found that this cooling ability varies significantly around the world and is influenced by tree species traits, urban layout and climate conditions.

“Our study busts the myth that trees are the ultimate panacea for overheating cities across the globe,” said Dr Ronita Bardhan, Associate Professor of Sustainable Built Environment at Cambridge's Dept. of Architecture.

“Trees have a crucial role to play in cooling cities down but we need to plant them much more strategically to maximise the benefits which they can provide.”

Previous research on the cooling effects of urban trees has focused on specific climates or regions, and considered case studies in a fragmented way, leaving major gaps in our knowledge about unique tree cooling mechanisms and how these interact with diverse urban features.

To overcome this, the authors of this study analysed the findings of 182 studies – concerning 17 climates in 110 global cities or regions – published between 2010 and 2023, offering the first comprehensive global assessment of urban tree cooling.

During the day, trees cool cities in three ways: by blocking solar radiation; through evaporation of water via pores in their leaves; and by foliage aerodynamically changing airflow. At night, however, tree canopies can trap longwave radiation from the ground surface, due to aerodynamic resistance and ‘stomatal closure’ – the closing of microscopic pores on the surface of leaves partly in response to heat and drought stress.

Variation by climate type

̽��ֱ��study found that urban trees generally cool cities more in hot and dry climates, and less in hot humid climates.

In the ‘tropical wet and dry or savanna’ climate, trees can cool cities by as much as 12 °C, as recorded in Nigeria. However, it was in this same climate that trees also warmed cities most at night, by up to 0.8°C.

Trees performed well in arid climates, cooling cities by just over 9°C and warming them at night by 0.4 °C.

In tropical rainforest climates, where humidity is higher, the daytime cooling effect dropped to approximately 2°C while the nighttime heating effect was 0.8 °C.

In temperate climates, trees can cool cities by up to 6°C and warm them by 1.5°C.

Using trees more strategically

̽��ֱ��study points out that cities which have more open urban layouts are more likely to feature a mix of evergreen and deciduous trees of varying sizes. This, the researchers found, tends to result in greater cooling in temperate, continental and tropical climates.

̽��ֱ��combined use of trees in these climates generally results in 0.5 °C more cooling than in cities where only deciduous or evergreen trees feature. This is because mixed trees can balance seasonal shading and sunlight, providing three-dimensional cooling at various heights.

In arid climates, however, the researchers found that evergreen species dominate and cool more effectively in the specific context of compact urban layouts such as Cairo in Egypt, or Dubai in UAE.

In general, trees cooled more effectively in open and low-rise cities in dry climates. In open urban layouts, cooling can be improved by about 0.4 °C because their larger green spaces allow for more and larger tree canopies and a greater mix of tree species.

“Our study provides context-specific greening guidelines for urban planners to more effectively harness tree cooling in the face of global warming,” Dr Ronita Bardhan said.

“Our results emphasize that urban planners not only need to give cities more green spaces, they need to plant the right mix of trees in optimal positions to maximize cooling benefits.”

“Urban planners should plan for future warmer climates by choosing resilient species which will continue to thrive and maintain cooling benefits,” said Dr Bardhan, a Fellow of Selwyn College, Cambridge.

Matching trees to urban forms

̽��ֱ��study goes further, arguing that species selection and placement needs to be compatible with urban forms. ̽��ֱ��orientation of the ‘street canyon’, local climate zones, aspect ratio, visible sky ratio and other urban features that influence the effects of trees all need to be carefully considered.

Although a higher degree of tree canopy cover in street canyons generally results in more cooling effects, excessively high cover may trap heat at the pedestrian level, especially in compact urban zones in high temperature climates. In such locations, narrow species and sparse planting strategies are recommended.

̽��ֱ��researchers emphasise that we cannot rely entirely on trees to cool cities, and that solutions such as solar shading and reflective materials will continue to play an important role.

̽��ֱ��researchers have developed an interactive database and map to enable users to estimate the cooling efficacy of strategies based on data from cities with similar climates and urban structures.

Reference

H Li et al., ‘Cooling efficacy of trees across cities is determined by background climate, urban morphology, and tree trait’, Communications Earth & Environment (2024). DOI: 10.1038/s43247-024-01908-4

While trees can cool some cities significantly during the day, new research shows that tree canopies can also trap heat and raise temperatures at night. ̽��ֱ��study aims to help urban planners choose the best combinations of trees and planting locations to combat urban heat stress.

Trees have a crucial role to play in cooling cities down but we need to plant them much more strategically to maximise the benefits which they can provide

Ronita Bardhan

hannahisabelnic via Flikr (Public domain)

Trees in an Indian city street. Photo: hannahisabelnic via Flikr (Public domain)

̽��ֱ��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

Licence type:

Public Domain

Is Democracy Dying?

fymj2 — Mon, 15 Apr 2024 11:22:18 +0000

2024 is the year of elections. A record number of elections will take place, with half the adult population of the world – some two billion people – having the chance to vote. Is this a milestone to be celebrated in our democratic history or are we at a crossroads where the fate of liberal democracy hangs in the balance?

Against a backdrop of polarising populist movements, the erosion of trust in traditional institutions and a decline of democratic norms, we asked: is democracy dying? Is the election of populists an expression of democracy or a breakdown of democracy? How resilient are our democratic institutions in the face of unprecedented challenges? Is the tension between liberal and democracy ultimately too great to resolve?

We addressed these questions in our second Vice-Chancellor’s Dialogues, hosted by Vice-Chancellor Professor Deborah Prentice on 24 April 2024.

Our speakers

David Goodhart, founding editor of Prospect magazine and Head of the Demography, Immigration and Integration unit at the think tank Policy Exchange. He is the author of ̽��ֱ��Road to Somewhere: ̽��ֱ��Populist Revolt and the Future of Politics.
Nabila Ramdani, award-winning journalist, broadcaster and academic. She is the author of Fixing France: How to Repair a Broken Republic.
Helen Thompson, Professor of Political Economy at the ̽��ֱ��. She is author of Disorder: Hard Times in the 21st Century.

̽��ֱ��discussion was chaired by Roger Mosey, Master of Selwyn College and former Editorial Director of the BBC.

̽��ֱ��Vice-Chancellor’s Dialogues

There are two purposes to these events. ̽��ֱ��first is to establish whether there is any common ground between people who may seem to be far apart. If we are to make progress in legislation or in understanding the world we live in, we need to identify where we agree as well as where we disagree. ̽��ֱ��second is to ensure discussions involve the widest range of viewpoints – that nothing, within the law, is taboo and that freedom of speech and of thought, and of academic debate, is upheld.

Watch our first event on whether assisted dying is compassionate, or dangerous for society >

On 24 April 2024, the second Vice-Chancellor’s Dialogues event grappled with the question: 'Is Democracy Dying?' ̽��ֱ��event is part of a series of dialogues about some of the most difficult issues of our time.

Cambridge Vice-Chancellor's Dialogues: Is democracy dying?

CamFest Speaker Spotlight: Dr Tom McClelland

zs332 — Wed, 20 Mar 2024 10:57:04 +0000

Tom McClelland is a lecturer in the Department of History and Philosophy of Science at the ̽��ֱ�� of Cambridge. He will be speaking about his and colleague Paulina Sliwa’s recent research findings on the much contested ground of who does the housework and what impact gender has in Seeing the mess: Gender, housework and perception at the Whipple Museum of the History of Science on Thursday 21st March 3-4pm.

Plastic Fantastic Cambridge

plc32 — Wed, 13 Mar 2024 13:48:55 +0000

Cambridge ̽��ֱ�� Association Football Club (CUAFC) will wear a design that copies the match kit from their 1905 Varsity fixture with Oxford for this year's 150th Anniversary Varsity match. But the shirts, socks and shorts for the 39th Women’s Varsity Match and the 139th Men’s Varsity Match in Cambridge on Friday 15th March are a modern marvel of recycling innovation.

AI trained to identify least green homes by Cambridge researchers

ta385 — Thu, 02 Nov 2023 08:00:00 +0000

‘Hard-to-decarbonize’ (HtD) houses are responsible for over a quarter of all direct housing emissions – a major obstacle to achieving net zero – but are rarely identified or targeted for improvement.

Now a new ‘deep learning’ model trained by researchers from Cambridge ̽��ֱ��’s Department of Architecture promises to make it far easier, faster and cheaper to identify these high priority problem properties and develop strategies to improve their green credentials.

Houses can be ‘hard to decarbonize’ for various reasons including their age, structure, location, social-economic barriers and availability of data. Policymakers have tended to focus mostly on generic buildings or specific hard-to-decarbonise technologies but the study, published in the journal Sustainable Cities and Society, could help to change this.

Maoran Sun, an urban researcher and data scientist, and his PhD supervisor Dr Ronita Bardhan (Selwyn College), who leads Cambridge’s Sustainable Design Group, show that their AI model can classify HtD houses with 90% precision and expect this to rise as they add more data, work which is already underway.

Dr Bardhan said: “This is the first time that AI has been trained to identify hard-to-decarbonize buildings using open source data to achieve this.

“Policymakers need to know how many houses they have to decarbonize, but they often lack the resources to perform detail audits on every house. Our model can direct them to high priority houses, saving them precious time and resources.”

̽��ֱ��model also helps authorities to understand the geographical distribution of HtD houses, enabling them to efficiently target and deploy interventions efficiently.

̽��ֱ��researchers trained their AI model using data for their home city of Cambridge, in the United Kingdom. They fed in data from Energy Performance Certificates (EPCs) as well as data from street view images, aerial view images, land surface temperature and building stock. In total, their model identified 700 HtD houses and 635 non-HtD houses. All of the data used was open source.

Maoran Sun said: “We trained our model using the limited EPC data which was available. Now the model can predict for the city’s other houses without the need for any EPC data.”

Bardhan added: “This data is available freely and our model can even be used in countries where datasets are very patchy. ̽��ֱ��framework enables users to feed in multi-source datasets for identification of HtD houses.”

Sun and Bardhan are now working on an even more advanced framework which will bring additional data layers relating to factors including energy use, poverty levels and thermal images of building facades. They expect this to increase the model’s accuracy but also to provide even more detailed information.

̽��ֱ��model is already capable of identifying specific parts of buildings, such as roofs and windows, which are losing most heat, and whether a building is old or modern. But the researchers are confident they can significantly increase detail and accuracy.

They are already training AI models based on other UK cities using thermal images of buildings, and are collaborating with a space products-based organisation to benefit from higher resolution thermal images from new satellites. Bardhan has been part of the NSIP – UK Space Agency program where she collaborated with the Department of Astronomy and Cambridge Zero on using high resolution thermal infrared space telescopes for globally monitoring the energy efficiency of buildings.

Sun said: “Our models will increasingly help residents and authorities to target retrofitting interventions to particular building features like walls, windows and other elements.”

Bardhan explains that, until now, decarbonization policy decisions have been based on evidence derived from limited datasets, but is optimistic about AI’s power to change this.

“We can now deal with far larger datasets. Moving forward with climate change, we need adaptation strategies based on evidence of the kind provided by our model. Even very simple street view photographs can offer a wealth of information without putting anyone at risk.”

̽��ֱ��researchers argue that by making data more visible and accessible to the public, it will become much easier to build consensus around efforts to achieve net zero.

“Empowering people with their own data makes it much easier for them to negotiate for support,” Bardhan said.

She added: “There is a lot of talk about the need for specialised skills to achieve decarbonisation but these are simple data sets and we can make this model very user friendly and accessible for the authorities and individual residents.”

Cambridge as a study site

Cambridge is an atypical city but informative site on which to base the initial model. Bardhan notes that Cambridge is relatively affluent meaning that there is a greater willingness and financial ability to decarbonise houses.

“Cambridge isn’t ‘hard to reach’ for decarbonisation in that sense,” Bardhan said. “But the city’s housing stock is quite old and building bylaws prevent retrofitting and the use of modern materials in some of the more historically important properties. So it faces interesting challenges.”

̽��ֱ��researchers will discuss their findings with Cambridge City Council. Bardhan previously worked with the Council to assess council houses for heat loss. They will also continue to work with colleagues at Cambridge Zero and the ̽��ֱ��’s Decarbonisation Network.

Reference

M Sun & R Bardhan, ‘Identifying Hard-to-Decarbonize houses from multi-source data in Cambridge, UK’, Sustainable Cities and Society (2023). DOI: 10.1016/j.scs.2023.105015

First of its kind AI-model can help policymakers efficiently identify and prioritize houses for retrofitting and other decarbonizing measures.

This is the first time that AI has been trained to identify hard-to-decarbonize buildings

Ronita Bardhan

Street view images of houses in Cambridge, UK, identifying building features. Red represents region contributing most to the 'Hard-to-decarbonize' identification. Blue represents low contribution.

̽��ֱ��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

Robots cause company profits to fall – at least at first

sc604 — Thu, 03 Aug 2023 10:05:12 +0000

̽��ֱ��researchers, from the ̽��ֱ�� of Cambridge, studied industry data from the UK and 24 other European countries between 1995 and 2017, and found that at low levels of adoption, robots have a negative effect on profit margins. But at higher levels of adoption, robots can help increase profits.

According to the researchers, this U-shaped phenomenon is due to the relationship between reducing costs, developing new processes and innovating new products. While many companies first adopt robotic technologies to decrease costs, this ‘process innovation’ can be easily copied by competitors, so at low levels of robot adoption, companies are focused on their competitors rather than on developing new products. However, as levels of adoption increase and robots are fully integrated into a company’s processes, the technologies can be used to increase revenue by innovating new products.

In other words, firms using robots are likely to focus initially on streamlining their processes before shifting their emphasis to product innovation, which gives them greater market power via the ability to differentiate from their competitors. ̽��ֱ��results are reported in the journal IEEE Transactions on Engineering Management.

Robots have been widely used in industry since the 1980s, especially in sectors where they can carry out physically demanding, repetitive tasks, such as automotive assembly. In the decades since, the rate of robot adoption has increased dramatically and consistently worldwide, and the development of precise, electrically controlled robots makes them particularly useful for high-value manufacturing applications requiring greater precision, such as electronics.

While robots have been shown to reliably raise labour productivity at an industry or country level, what has been less studied is how robots affect profit margins at a similar macro scale.

“If you look at how the introduction of computers affected productivity, you actually see a slowdown in productivity growth in the 1970s and early 1980s, before productivity starts to rise again, which it did until the financial crisis of 2008,” said co-author Professor Chander Velu from Cambridge’s Institute for Manufacturing. “It’s interesting that a tool meant to increase productivity had the opposite effect, at least at first. We wanted to know whether there is a similar pattern with robotics.”

“We wanted to know whether companies were using robots to improve processes within the firm, rather than improve the whole business model,” said co-author Dr Philip Chen. “Profit margin can be a useful way to analyse this.”

̽��ֱ��researchers examined industry-level data for 25 EU countries (including the UK, which was a member at the time) between 1995 and 2017. While the data did not drill down to the level of individual companies, the researchers were able to look at whole sectors, primarily in manufacturing where robots are commonly used.

̽��ֱ��researchers then obtained robotics data from the International Federation of Robotics (IFR) database. By comparing the two sets of data, they were able to analyse the effect of robotics on profit margins at a country level.

“Intuitively, we thought that more robotic technologies would lead to higher profit margins, but the fact that we see this U-shaped curve instead was surprising,” said Chen.

“Initially, firms are adopting robots to create a competitive advantage by lowering costs,” said Velu. “But process innovation is cheap to copy, and competitors will also adopt robots if it helps them make their products more cheaply. This then starts to squeeze margins and reduce profit margin.”

̽��ֱ��researchers then carried out a series of interviews with an American medical equipment manufacturer to study their experiences with robot adoption.

“We found that it’s not easy to adopt robotics into a business – it costs a lot of money to streamline and automate processes,” said Chen.

“When you start bringing more and more robots into your process, eventually you reach a point where your whole process needs to be redesigned from the bottom up,” said Velu. “It’s important that companies develop new processes at the same time as they’re incorporating robots, otherwise they will reach this same pinch point.”

̽��ֱ��researchers say that if companies want to reach the profitable side of the U-shaped curve more quickly, it’s important that the business model is adapted concurrently with robot adoption. Only after robots are fully integrated into the business model can companies fully use the power of robotics to develop new products, driving profits.

A related piece of work being led by the Institute for Manufacturing is a community programme to help small- and medium-sized enterprises (SMEEs) to adopt digital technologies including robotics in a low-cost, low-risk way. “Incremental and step changes in this area enable SMEs to get the benefits of cost reduction as well as margin improvements from new products,” said co-author Professor Duncan McFarlane.

̽��ֱ��research was supported by the Engineering and Physical Sciences Research Council (EPSRC) and the Economic and Social Research Council (ESRC), which are both part of UK Research and Innovation (UKRI). Chander Velu is a Fellow of Selwyn College, Cambridge. Duncan McFarlane is a Fellow of St John's College, Cambridge.

Reference:
Yifeng P Chen, Chander Velu, Duncan McFarlane. ‘ ̽��ֱ��Effect of Robot Adoption on Profit Margins.’ IEEE Transactions on Engineering Management (2023). DOI: 10.1109/TEM.2023.3260734

Researchers have found that robots can have a ‘U-shaped’ effect on profits: causing profit margins to fall at first, before eventually rising again.

It’s important that companies develop new processes at the same time as they’re incorporating robots, otherwise they will reach this same pinch point

Chander Velu

kynny via Getty Images

Robots on a manufacturing line

̽��ֱ��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