This ESRC IAA project will be exploring ways in which the Southway area of Guildford can be improved.
The residential area of north-west Guildford suffers from high volumes of commuter traffic, issues with parking and very poor air quality at peak traffic times, particularly at the western end. It contains locations that have some of the worst scoring indices of deprivation within the UK.
The University of Surrey has been engaging with these communities over a number of years, to identify ways in which it can offer support. Two years ago Professor Paul Krause and colleagues started an umbrella project, NW Guildford 2030 to engage with key stakeholders in the region, identify what matters most to them in rebuilding a thriving sense of place, and build a portfolio of research projects that can directly help them.
Environment and green space came up as priorities amongst all age groups in the community from high-school students to senior citizens and it is felt that enhancements to green infrastructure have the highest potential payback for quality of life. As a result of this, they initiated a “Greening Southway” community engagement project to focus initial activities in.
This short ESRC IAA funded element of Dr Ratcliffe’s work centres on a series of interviews with residents/local stakeholders, analysing questionnaires and interviews and working with the local stakeholders to identify a small number of feasible interventions that could enhance the quality of life for residents and users of the Southway area.
Although the team cannot fund infrastructural improvements in the area, they can advise and facilitate and the main goal in this two-month project is to work with the community to help them identify some realistic improvement opportunities.
I gained BSc and MSc degrees in Psychology from Goldsmiths, University of London, before completing my PhD in Environmental Psychology at University of Surrey in 2015. I then undertook two postdoctoral research positions: first in the Department of Psychology, University of Tampere (Finland), funded by the Leverhulme Trust, and second at the Dyson School of Design Engineering, Imperial College London (UK). In 2019 I returned to University of Surrey as Lecturer in Environmental Psychology.
As an environmental psychologist I focus mainly on restorative environments, place experience, and links between environment and wellbeing, including in the workplace. I also conduct research on consumer and user experience, especially with regard to improving perceptions and behaviours around goods and services. I am increasingly interested in links between consumer behaviour and sustainability. Before becoming a psychologist I trained in art and design, and I combine aspects of my work in environmental psychology with design thinking and research.
In the course of my work I have collaborated with a number of non-academic organisations, including the National Trust, Surrey Wildlife Trust, Heathrow and Gatwick Airports, the Cabinet Office, and Nestlé.
I graduated in 1977 with First Class Honours in Pure Mathematics and Physics from the University of Exeter. Following that I studied for a PhD in Geomagnetism under Geraint Rosser at the same university.
During my career I have worked at three internationally leading independent research laboratories:
- The National Physical Laboratory (1980-87);
- The Imperial Cancer Research Fund (1989-1996);
- Philips Research Laboratories, UK (1996-2003).
I greatly enjoyed my seven years at the National Physical Laboratory, working with some dedicated and highly talented scientists. At the end of those seven years I had achieved an order of magnitude improvement of the repeatability of the josephson voltage standard, with also a significantly improved ease of use and reduction in liquid helium consumption when performing the measurements. However, although quantum metrology is a fascinating area, I could not see any potential for significant advances in the underlying physics, so I went for a change.
Theory and practice of artificial intelligence
I started by working for two years at the University of Surrey within their Formal Methods of Software Engineering Group. What I actually did was more in the line of automated theorem proving, spending my time working with Ron Knott on using Prolog to automatically generate behaviours implied by system specifications written in set theory and formal logic. Specification verification tools are way ahead if that now, but it was a fun introduction to the challenges of building automated reasoning systems. Incidentally, Ron is still maintaining the longest running website on recreational mathematics.
I moved on to the Imperial Cancer Research Fund (now Cancer Research UK) in 1989 to work on automated decision making and diagnosis for health care. We were typically looking at non-classical logics and symbolic reasoning in order to make the "arguments" supporting candidate decisions explicit. This lead to some of the earliest published work on computational models of argumentation; an area of research that has grown significantly since those days. Our own work defined a category theoretic semantics for our model of argumentation. We had very extensive collaborations across the research community in models of decision making and reasoning under uncertainty, and my introductory (and very successful at the time) text book with Dominic Clark on Representing Uncertainty, an AI Approach spun out of that.
After seven years at ICRF it was, of course, time to move on again. I took up a post at Philips Research Laboratories, Redhill, to work as a Principal Scientist within Paul Gough's Software Engineering and Applications research group. Sounds a bit like a change of topic, but was not in fact. Machine automation and reasoning were still key here: "robots" to automate the testing of consumer products; semantic reasoning to automatically generate links between entities in hierarchies of documents; bayesian models for software quality assessment. The last of these initiated a long standing collaboration between myself, and Norman Fenton and Martin Neil at City University and Agena Ltd.
2001 saw me moving to a joint appointment with Philips and the University of Surrey, with the aim of strengthening collaboration on computer science research between the two organisations. Sadly, the end of 2001 saw the beginning of the end of Philips Research's once world class research laboratory at Redhill. Promotion to Senior Principal Scientist was a short lived pleasure, but a climax to a wonderful time at Philips. As the research laboratory was gradually wound down, so I progressively moved to full time at the University of Surrey from the beginning of 2003.
Of course, a big difference between industry-focused research laboratories and an academic department is that in academia one is not constrained to work within defined remits of a specific industry sector (although both NPL and Philips Research at their best did indeed support a level of blue sky research). So the move to academia did of course give me more freedom in my trajectory. Despite the recent high-profile successes in AI, I believe there are some major challenges. Two key ones for me are: explainability/accountability of AI supported decision making; and, bias.
Addressing the former issue has been a major influencer of the approaches I have taken. Going back to our work on toxicological risk prediction with Lhasa Ltd, for the pharmaceutical industry an ability to classify novel chemical compounds according to potential risk classes had little value unless the reasons ("arguments") for those classifications were made explicit to the analysts. Moving on to more recent work, my work with Nick Ryman-Tubb during his PhD and subsequently is showing that 20 years' research on fraud detection in academia has not resulted in any significant advances when assessed according to industrially relevant metrics [Ryman-Tubb, Krause and Garn, 2018]. We have also shown <<citation pending>> that unless there are significant changes to the regulatory environment, the financial sector will simply continue to consider the current level of fraud as an acceptable cost of business - with no account being taken that fraud is in effect a multi-billion dollar industry that is funding terrorism and organised crime. The research challenge is to build AI/data analytic tools that help us gain understanding of the fraud vectors themselves, and also explicate the real impact of this level of crime to help facilitate change to the status quo.
The issue of bias is pernicious in AI. The problem here is that, obviously, the models are only as good as the data they are trained on. Never mind the irritation of an e-commerce recommending you products that are way off topic for your specific personality. More critical is the potential risk for a health care advisor to judge a health care scenario on the basis of a data set that has been obtained from a predominantly middle class western population. Within that population there will be ethnic groups that will have had little representation within the training sets. Even worse, there may be pressure to apply such a model on a global basis to populations that have absolutely no representation in the training of the model.
This is a real challenge in academic research as it is so hard to spend the length of time needed to collate, gain regulatory approval and quality check high quality data on a global basis. However, we are making progress on this and for the last two or three years I have been supporting Lilian Tang's work on diabetic retinopathy in collating extensive retinal image sets from disparate regions across the globe [Lutfiah Al Turk, Paul Krause, Su Wang, Hend Alsawadi, Abdulrahman Zaid Alshamrani, Tunde Peto, Andrew Bastawrous, and Hongying Lilian Tang, Automated Progression Analysis Across Three Nations, to be submitted].
Deep Learning has had a lot of successes. There is so much hype around it that it almost seems that the public eye is equating deep learning with AI. But simply thinking that throwing massive data sets at smart algorithms will generate knowledge is a big mistake. Our group's work on diabetic retinopathy, the projects mentioned above, and others, support the conviction that we must still support human-machine co-creation of knowledge. Big data sets, and smart algorithms are necessary, but they are not sufficient for the generation of machines that demonstrate "intelligent" problem solving. Now, working collectively within the NICE group in the Department of Computer Science here at Surrey, we are building out a suite of capabilities that will continue to help us build machines that can communicate and collaborate with human beings to solve complex problems. Consider, for example, the urgent need to gain deeper understanding of the links between biodiversity and the provision of ecosystem services. With Alireza Tamaddoni Nezhad, we have capability for mining ecological networks using Inductive Logic Programming and Meta-heuristic reasoning. Through Sotiris Moschoyiannis, we have an emerging toolset for the identification of the system levers or “drivers” which have high influence on the overall system behaviour. Yunpeng Li now strengthens our Bayesian analytic capability; still a powerful method for ensuring assumptions are correctly captured when reasoning with complex data sets. André Grüning gives further support on techniques for driving dynamical systems into preferred states, perhaps using reinforcement learning to identify interventions to transition a degraded ecological network into one offering enhanced functionality and resilience.
I fundamentally do not believe we can learn how to maintain a human presence in the stunningly beautiful biosphere that we are blessed with, without a richer suite of tools from AI -- and ones with which we can co-create knowledge and understanding. We won't survive on this world without them. But, of course, the world may well survive without us...
Dr Chris Jones is a Senior Lecturer in Social and Environmental Psychology, with particular interests in attitudes and behaviours towards energy and environment.
He gained his first degree in Psychology (BSc) at the University of Birmingham (1999-2002) before moving to the University of Sheffield to complete a Master’s degree in Psychological Research (2002-2003) and a PhD in Social Psychology (2003-2007). His PhD, completed under the supervision of Prof. J. Richard Eiser, focused on understanding more about the nature and process of attitude formation in novel environments.
Upon completing his PhD, Chris completed a 4-year post-doctoral position on the ‘Understanding Risk: Climate change and energy choices’ project (2007-2010). It was this multi-centre (Cardiff, Sheffield & UEA), multi-disciplinary project that first stimulated Chris’s research interests in public attitudes towards environmental change.
Following his appointment as Lecturer in Social and Environmental Psychology at the University of Sheffield (2011), Chris continued to develop these interests and developed two key strands of research: (1) Assessing attitudes and behaviour towards energy supply and demand side technology options; and (2) Assessing the factors that facilitate and inhibit the promotion of more sustainable lifestyles. The applied relevance of these topics has led Chris to develop a number of fruitful collaborations with academics in other disciplines, as well as a number of non-academic stakeholder groups (e.g. business and industry).
Chris joined the University of Surrey in the summer of 2017.
Alongside his research and teaching roles, Chris is the Impact Lead and the Employability Lead for the School of Psychology.
Professor Prashant Kumar is Associate Dean (International) for the Faculty of Engineering and Physical Sciences, Chair in Air Quality and Health and the founding Director of the Global Centre for Clean Air Research (GCARE) at the University of Surrey, UK. He is the Head of the GCARE’s Air Quality Laboratory and the Deputy Director of Research for the Department of Civil & Environmental Engineering. Since March 2018, he is also an Adjunct Professor at the School of Engineering at the Trinity College Dublin in Ireland.
He received his PhD (Engineering) from the University of Cambridge, and an MTech (Environmental Engineering & Management) from Indian Institute of Technology (IIT) Delhi. Prior to his PhD, he worked at a research instutute and in industrial sector for about 8 years. After his PhD, he joined University of Surrey as Lecturer (2009-2012), and subsequently worked as Senior Lecturer (2012-2015) and Reader (2015-2017).
His fundamental and application oriented crossdisciplinary research is focused at the interfaces of clean air engineering/science, human health and smart/sustainable living in cities/megacities. His research builds an understanding of the formation and emission of particles, both from vehicle exhausts and non-vehicular sources. He investigates their contribution to pollution, especially in megacity contexts. He is developing approaches to low-cost sensing and contributing to the development of exposure control technology and guidelines for policymakers to curtail pollution exposure in cities, with associated health benefits.
His current research projects are focused in broad multidisciplinary areas of air pollution monitoring/modelling, low-cost sensing, nature-based solutions, climate change mitigation and developing innovative technological and passive (e.g. green infrastructure) solutions for air pollution exposure control for both developing and developed world.
With over 210 articles in top-ranked journals (h-index 51; i10-index 139; citations >8900), his research has secured over £8.5 million of individual funding from the RCUK (e.g, EPSRC, ESRC, NERC, MRC, HEFCE, British Council, Innovate UK, Research England), industry and international funding bodies (e.g., European Commission, Qatar National Research Foundation, Commonwealth Commission, FAPESP). He has developed a network of collaborators across four continents, serving on editorial boards of several international journals and scientific evaluation panels of numerous funding agencies.
He is advising local/national/international agencies on air pollution and urban nexus and his research has featured in well-read media outlets such as the BBC and The Times.
Once they have identified and prioritised improvements in collaboration with the community, the team will assist in the preparation of two submissions for funding – one for continued and more substantial support from the University and one to fund the interventions.
For this specific two-month project, the team are aiming for three core results:
- The co-creation of a documented shared vision for Southway
- A measurable increase in the level of engagement with the community
- Submission of two funding proposals as specified above.
The proposed project will be an important vehicle for both demonstrating the value of the University of Surrey's Environmental Psychology and its related research.
It will build a relationship between the social sciences researchers and those working on data science, sensor technology and Internet of Things because these technologies may be used to demonstrate the relationship between measurable environmental factors such as air quality and enhanced feelings of well-being.
The project will showcase the relevance of the team's work to the wider community by showing how research can be used to evidence and strengthen support to empower the community in their ambitions to enhance their environment and sense of place.
Impact Acceleration Account awarded projects
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