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Our projects address research challenges in the fields of artificial intelligence, robotics and human-machine systems.

Funded projects

The following projects highlight the research activity which is currently underway.

This project aims to develop an active reinforcement learning algorithm that will support the growth of a robot’s cognitive model for enhanced localisation and fail-safe navigation. It will do so through continuously interacting with environments without explicitly building large-scale high-resolution maps.

The vision is a robot that is cognitively aware of “danger” levels in different regions and capable of navigating without building a prior map—mapless navigation. With this ability, the robot’s path can be optimally decided to allow it to identify “safe” or “danger” zones and ensure localisation confidence, avoid poor localisation, and ensure fail-safe autonomous navigation.

Reliable autonomous navigation for autonomous vehicles in an unknown environment requires highly accurate robot localisation and environment mapping. Global navigation satellite system (GNSS) sensors are commonly used for outdoor localisation and navigation, and simultaneous localisation and mapping (SLAM) is widely used for GNSS-denied environments by taking data from different sensors e.g. LiDAR, vision odometry, IMU.

Academic team

Dr Ze Ji

This project is funded by Spirent Communications.

This project with the Intellectual Property Office (IPO) aims to understand the feasibility, technical complexities, and effectiveness of artificial intelligence (AI) solutions during prior art searching of patent applications. IPO is interested in a proof-of-concept for an AI-powered due diligence check to aid online patent filing and patent examiner prior art searching processes, to reduce time and cost and improve process quality.

Specific objectives of the study

  • Evaluate viability of AI technologies for patent prior art searching
  • Test different approaches to find the most effective algorithms
  • Fully test and evaluate an optimal algorithm.

The study concludes that with current AI tools, it is not feasible to deliver a fully automated solution to the patent application filing process. Patents are manually classified by examiners, but this research shows that an automated classification task produces high classification accuracy. This classification task could be embedded into the online patent pre-filing process to allow an easier undertaking of due diligence checks.

Read the report.

Academic team

Professor Rossi Setchi
Professor Irena Spasić
Dr Fernando Loizides
Dr Jeffrey Morgan

This project is funded by the Department for Business, Energy and Industrial Strategy’s Regulators Pioneer Fund.

This project aims to develop innovative computational methods and magnetic resonance (MR) techniques to reveal new non-invasive markers of brain microstructure.

Main objective

To provide non-invasive tools for improved diagnostic information as powerful as invasive techniques.

To address key limitations of current MR for microstructure imaging, the project proposes a three-component shift of paradigm:

  • Employing detailed simulation of the tissue architecture to encode the forward problem (from tissue microstructure to MR signal)
  • Use modern AI to solve the inverse problem
  • Estimate of uncertainty to quantify ambiguity and significance of the results.

Nature has built one of the most extraordinary machines: the brain, using basic cellular components of neurons and glia. Understanding how these individual components are designed (cell morphology) and assembled (tissue microstructure) is the key to understanding both the brain's structure and function, and more importantly its degeneration/dysregulation in diseases. However, it is currently impossible to quantify tissue microstructure in a non-invasive way. Standard methods like histology can reveal microscopic characteristics of tissue architecture but at the cost of invasive interventions like biopsies and limited coverage of the investigated tissue, undermining diagnostic power.

This project is developed around the Future Leaders Fellowship awarded to the principal investigator.

Academic team

Dr Marco Palombo

This project is funded by UK Research and Innovation.

This project aims to help develop cyber systems security, culture and processes that work for people instead of placing responsibility and blame on the user. The project will build a capability to develop and test technology and best practices that support the user.

A research associate and PhD studentship have been appointed to work on sub-projects of the Airbus Cyber Psychology and Human Factors project including:

Research associate

  • Development of a human factors cyber security assessment tool
  • Development of cyber security metrics and visualisations
  • Experimental intervention work.

PhD studentship

  • Development of a human factors cyber security assessment tool
  • Development of cyber security metrics and visualisations
  • Cyber security behaviour-change experimental intervention
  • Developing adaptive human-machine interfaces to reduce cyber influence technique susceptibility.

Academic team

Professor Phil Morgan
Dr Phoebe Asquith
George Raywood-Burke (PhD student)
Laura Bishop (PhD student funded by Cardiff University. Working one day per week at Airbus)

This project is funded by Airbus and Endeavr Wales

This project aims to automate and digitize the structural survey process for substandard bridges in the UK using autonomous drones, which together with existing structural information will have the embedded function of 3D model reconstruction and data visualisation.

Image processing technology and data analytics, couples with deep learning algorithms will be developed to determine the condition of the asset elements. This will be used for the identification of defects and the capability will be integrated into the 3D models and data visualisation, with the creation of a digital twins platform to collect and visualise multi-source data continuously, to provide quick risk assessment and predictive maintenance.

The number of substandard bridges in the UK has increased significantly with an estimated UK Government spend of ~£890 million on their maintenance. Of the more than 35,000 bridges of the UK rail network, most are old with more than half constructed over 100 years ago. It is critically important to conduct timely structural surveys for these bridges to understand their structural safety and integrity and decide on relevant maintenance options.

Academic team

Professor Haijiang Li
Dr Ze Ji
Dr Abhishek Kundu

This project is funded by UKRI Knowledge Transfer Partnership and Centregreat Rail Ltd.

This project aims to explore the potential of information and communications technologies (ICT) to enhance maternal and child health (MCH) and wellbeing during the antenatal and postnatal period in South Africa.

Main objectives

  • Develop an interdisciplinary network to explore, co-design, share, inspire and develop innovative ways to address MCH challenges through digital health
  • Identify and engage with key stakeholders through a co-design enquiry approach to further understand the complex social, structural, and economic factors that can strengthen or weaken MCH digital interventions
  • Explore, create, and test a set of creative and alternative scenarios of emerging digital health tools and services to identify emerging research priorities, research questions, and role of ICTs for addressing social factors of MCH in South Africa.

The support of MCH through digital interventions is widespread, but the impact of these interventions in low-income communities is limited, which may be the result of the top-down nature of digital health development. The project will form an interdisciplinary, cross-cultural, and cross-geographical network of researchers, technology designers, healthcare professionals, community stakeholders, policy makers and grassroots organisations.

Academic team

Dr Nervo Verdezoto Dias
Professor Paula Griffiths
Dr Emily Rousham
Dr Emma Haycraft
Professor Tebogo Mothiba
Professor Shane Norris
Dr Alastair van Heerden
Dr Nicola Mackintosh
Dr Qian Gong
Dr Diane Levine
Dr Melissa Densmore
Dr Yaseen Joolay
Professor Simone Honikman
Dr Kate Boyer
Dr Mercedes Torres Torres
Dr Dawn Mannay
Professor Fiona Ross
Dr Carolina Fuentes
Dr Kathryn Jones

This project is funded by the Engineering and Physical Sciences Research Council.

This project aims to design a control system model of physical activity (PA) intervention. The model will help validate and construct a system identification experiment with risk groups in Ecuador that will estimate suitable model properties and adjust to social, cultural, and economic settings.

What it will deliver

The project will deliver:

  • A paper for the Journal of Medical Internet Research and structure an IEEE Transactions on control systems and technology
  • A workshop in ACM CHI’22 and in Cardiff University in collaboration with EPSRC funded GetAMoveOn Network+ to explore opportunities between HCI researchers and control engineers
  • An impact case study to demonstrate the difference this research makes to risk groups in Ecuador.

Many physical activity (PA) interventions utilising smartphone apps and trackers are designed for sedentary populations in developed countries, however, these tools don’t have the same financial, social and cultural acceptance in developing countries. The proposed control systems model will rely on social cognitive theory based on experimental datasets collected in the USA and UK.

Academic team

Dr Parisa Eslambolchilar

This project is funded by The Leverhulme Trust.

We developed an ecologically-appealing and semantically-rich web-based task called SECURITY in which participants complete a series of eight acronym-based checks on an email that contains potentially sensitive information. In our project, we carried out novel experiments needed to benchmark SECURITY to learn whether our new task produces similar findings to existing standards.

Using interruption complexity effects to benchmark SECURITY against similar tasks, we find that participants make fewer errors in the semantically-rich email task, but resumption times are slower for more complex interruptions. Establishing a procedural task with an authentic context will allow future research into how to minimise action slips that may pose a risk to information security.

Academic team

Dr Candice Morey
Dr Helen Hodgetts
Dr Sandy Gould
Professor Phil Morgan
Professor Dylan Jones

The primary objective of this project is to develop a better understanding of how to design and deploy a sustainable IoT network in a remote jungle environment with harsh conditions. We deployed an IoT network with three sensors and three network extension mesh routers supported by a gateway to push data to the cloud. We wanted to understand what kind of IoT network would ideally be suited to establish a forest observatory to enable sustainable sensors data collection and wireless communication. We would like to understand potential network design and topology, estimated costs, energy requirements, and other constraining factors that may need to consider when deploying an IoT network in a jungle. Our long-term plan is to develop a forest observatory that has the capability to observe animals and the environment through heterogeneous sensors at scale to facilitate bioscience research and wildlife conservation activities. This project aims to collect data over 24 months period of time.

Academic team

  • Dr Charith Perera
  • Professor Omer Rana
  • Professor Benoit Goossens
  • Dr Pablo Orozco-terWengel

This project is funded by the Engineering and Physical Sciences Research Council (EPSRC).

This project aims to further the understanding of the effects of task switching and interruption on the performance of cyber security professionals, who often work under high pressure with sensitive information.

Like many computer users in the workplace, cyber security professionals often switch and alternate between different tasks i.e. computer-based multitasking. It is crucial to understand the effects of task switching and interruption for cyber security professionals and to identify ways to mitigate them.

Key research questions

This project addresses key research questions:

  • Focusing on task switching and interruption, what are the main cause(s) of harmful effects to the performance of cyber security professional when alternating between different computer-based tasks?
  • Which cyber security tasks are most impacted by disruption?
  • Can key factors identified by survey and boundary conditions (e.g. time pressure, cognitive workload) be detected in real-life task performance?
  • How can issues that have already been identified be mitigated within the cyber security context, through human and/or human-machine training system (re-) design?

Academic team

Professor Phil Morgan
Professor Dylan Jones OBE
Dr Candice Morey
Dr Qiyuan Zhang
Craig Williams (PhD student)

This project is funded by the National Cyber Security Centre (NCSC), a part of GCHQ.

This project explores how human dignity may be impacted by an AI-based decision support system for post-COVID-19 health certification. It examines the challenging possibility of representing human dignity as algorithms to determine behavioural changes to help understand the impact of an AI-based decision support system.

Drawing from law and moral philosophy, we relate the definition and content of human dignity to two aspects:

  • Recognition of the status of human beings as agents with autonomy and rational capacity to exercise judgement, reasoning, and choice
  • Respectful treatment of human agents so that their capacity is not diminished or lost through interactions with or use of the technology.

The project identifies components, sub-components, and related concepts of human dignity to translate into algorithms, which are used to design an agent-based behavioural simulation model of the health certification process and AI-based decision support system. The simulation model uses scenarios that indicate the loss of human dignity (e.g. coercion, manipulation, deception, loss of autonomy).

Key findings

The project identified:

  • Several legal-philosophical aspects that form human dignity, mainly the status of humans as autonomous agents with rational capacity. Respectful treatment where decisions are made in a person’s interest would constitute a system which treats human dignity fairly
  • An algorithmic design of a human dignity-aware decision support system (DSS), with pre-conditions simulation for a human dignity-aware DSS, based on agent-based modelling
  • Three use case scenarios to represent real-life contexts of interactions with a human dignity-aware DSS to access a vaccine and obtain a vaccine credential.

Academic team

Dr Ozlem Ulgen
Dr Carolina Fuentes Toro
Dr Kai Xu
Dr Ghita Berrada
Dr Okechukwu Okorie
Dr Robin Renwick

This project is funded by SPRITE+ through the Engineering and Physical Sciences Research Council.

This project aims to improve our understanding of human response, capabilities and limitations relating to artificial intelligence (AI) with focus on explainability and interpretability. When interacting with AI representations augmented with different degrees and types of explainability to enhance interpretability, a better understanding of effectively measuring human performance and behaviour is needed.

Addressing these key challenges will enable the effective design of studies that measure explainability and interpretability of AI to develop future models and theories.

Project’s main goals

  • Interim literature review: undertake initial literature review on the psychological aspects of AI including explainability and interpretability with focus on the knowns and key unknowns, and scoping of what research questions need addressing. Use-cases to be provided by Airbus
  • Final literature review and research methodology report: extended review on the psychological aspects of AI including explainability and interpretability with scoping of an appropriate methodology/methodologies linked to a use-case provided by Airbus
  • Study report: conduct a usability/evaluation study using the proposed methodology, possibly linked to one use-case, with human participants consisting of undergraduate students and/or a small sample of SMEs provided by Airbus.

Academic team

Professor Dylan Jones OBE
Professor Phil Morgan
Dr Mark Johansen
Dr Job van der Schalk
Dr Qiyuan Zhang

This project is funded by Airbus.

The research focused on the need to build safe systems for autonomous vehicles (AVs) in the future. We know that AVs will need to co-exist and share the road with human-driven vehicles and that some AVs might be partially/conditionally autonomous (so a human driver will be in control some of the time).

This research looked at the challenge of ensuring AVs make safe and appropriate driving decisions in any traffic situation by making them reactive and able to customise their decisions. It aimed to gather data from smart road infrastructure on features of the ‘other road users’ based on characteristics that typically signify age, gender and driving experience and then build models that allowed for variables in human behaviour presented by those human drivers rather than interacting on a ‘one-size-fits-all’ attention and reaction model.

Academic team

  • Dr Hantao Liu
  • Professor Phil Morgan
  • Professor Mara Tanelli

This project is funded by The Royal Society.

We know that interruptions are disruptive, and it can be difficult to quickly and accurately resume what we were doing after they occur. This disruption can be especially consequential in safety and security-critical contexts.

Removing interruptions is not possible in most contexts, so instead we need to focus on how we can minimise their disruptiveness. In this project, we investigate how computer-based tasks can be modified to make resuming after interruptions quicker and less error-prone.

Main research questions:

  • Does showing people the part of a task they were looking at before they were interrupted help them to resume more quickly and accurately?
  • Does adding annotations that show the order of previous interactions with a task help people resume more quickly and accurately after an interruption?

Our results suggest these techniques might be able to improve the accuracy of resumption after interruption. However, they do not enable people to resume more quickly, because the additions to the interface require additional time to interpret.

Alongside this research, we also investigated whether browser-based eye tracking with commodity webcams is useful for conducting remote studies. Our results were, unfortunately, inconclusive.

Academic team

Dr Sandy Gould
Dr Helen Hodgetts (Cardiff Met)
Dr Candice Morey
Professor Dylan Jones
Professor Phil Morgan

This project aims to develop new inter-culturally appropriate and acceptable strategies to address the dietary risks of anaemia and excess energy intake in infants and young children aged 6–23 months through healthy complementary feeding in Peru.


The project’s specific objectives are:

  • Identify the socio-cultural, behavioural and environmental influences on infant and young child nutrition and feeding practices in two distinct Peruvian regions
  • Develop, integrate and pilot new strategies to address the double burden of malnutrition among infants and young children through participatory design methods and prototyping interventions with families, community childcare and health facilities
  • Inform the development of feeding guidelines for children under 2 years of age, currently under review by the Peruvian Ministry of Health, through mapping global, national and local policy and incorporating Double Duty Actions to address current dietary risks
  • Work in partnership with local government health services and stakeholders to develop capacity to implement strategies, recommendations and support participatory approaches to infant and young child feeding interventions.

Peru is burdened by malnutrition and micronutrient deficiencies, especially anaemia, and a rapidly increasing prevalence of overweight and obesity. Early life nutrition is key to ensure optimal growth and reduce the risk of diet-related diseases throughout a life. Changing environments and dietary and nutrition transition increases the risk of infant micronutrient deficiency, with the additional risk of excess energy intake leading to overweight and obesity. This growing threat has led to global policy recommendations on Double Duty Actions, which reduce undernutrition, overweight and obesity, and diet-related non-communicable diseases.

Academic team

Dr Emily Rousham
Dr Nervo Verdezoto Días
Professor Paula Griffiths
Dr Ines Varela-Silva
Dr Emma Haycraft
Professor Michelle Holdsworth
Hilary Creed-Kanashiro
Rossina Pareja
Dr Doris Hilda Delgado Perez
Dr Violeta Magdalena Rojas Huayta
Professor Mg Luzvelia Alvarez Ortega
Professor Dr Teresita Vela López

This project is funded by the Medical Research Council via Loughborough University.

Graph neural networks (GNNs) are the standard framework for learning from relational data (i.e. data that explains how objects are related). Similarly, description logics are a highly popular framework for symbolic reasoning in relational domains. While these frameworks deal with the same type of data, they do so in very different ways. The aim of this project is to study how their complementary strengths can be combined, by using the representations learned by GNNs to allow for a kind of common-sense reasoning with Deep Learning (DL), allowing us to draw plausible conclusions which go beyond what can be logically deduced.


  • Study how GNNs can be used to obtain embeddings of relational patterns that support rule interpolation in an effective way.
  • Study the theoretical foundations of interpolative reasoning with relational pat- terns, with a particular emphasis on developing model-theoretical characterisations and de- signing efficient inference methods.
  • Carry out an evaluation to assess to what extent interpolative reasoning allows us to improve the predictive accuracy of existing rule based methods.

Academic team

This project is funded by the Leverhulme Trust.

THe INcident Command Skills (THINCS) is a system that supports the development and evaluation of psychological skills for incident commanders in the UK Fire and Rescue Service.  These skills include communication, decision-making and leadership.  The system was co-produced by Cardiff University and the National Fire Chiefs Council (NFCC).  Philip Butler led the development of THINCS during his ESRC-funded PhD, which was supported by the NFCC.  The aim of the ESRC IAA project was to promote THINCS nationally and internationally.

As part of the project, Cardiff University Research and Innovation Services helped to both develop a non-commercial THINCS licence and to transfer the issuing rights for this licence to the NFCC.  This enables THINCS to be readily available to all UK Fire and Rescue Services.  THINCS has also now been adopted by the Fire Service College (owned by Capita) as part of their suite of training courses for UK and international firefighters; and Philip Butler has trained their trainers in the use of THINCS.  During the project, he also gave THINCS training to many different UK Fire and Rescue Services, to the Atomic Weapons Agency Fire and Rescue Service, Bristol Airport Rescue and Firefighting Service, and Gibraltar Fire and Rescue Service.

Another part of the project involved Paul Allen generating a short film on the development and use of THINCS.  The intended audience for the film is firefighters, incident commanders, UK and international Fire and Rescue Services.  The film features Dr Philip Butler and Dr Sabrina Cohen-Hatton, who is an Honorary Fellow of Cardiff University and supervised Philip Butler, together with Professor Rob Honey.  It also features the South Wales Fire and Rescue Service.

Academic team

  • Professor Rob Honey
  • Dr Philip Butler
  • Dr Sabrina Cohen-Hatton

This project is funded by the Economic and Social Research Council, with additional funds received from the BBSRC Innovator of the Year Award 2018.

This project addresses the development of resilient built environments focusing on both smart home and office environments. The project involves two user partners: Building Research Establishment (BRE), focused on the smart home domain, and Cube Control Ltd., focused on the smart office domain.

The project explores how to add layers of resilience to built environments in the context of the Internet of Things (IoT), on which smart built environments such as homes and office buildings depend heavily to reliably sense and monitor their surroundings. Such dependencies create significant risk; malicious parties could tamper with IoT devices and systems to report incorrect data to control systems, creating significant risk to built environments. The development of resilient built environments by creating multiple layers of resilience is needed. Resilient means that if a malicious party may manipulate some IoT devices, the rest of the IoT system will be able to protect and maintain its functionality with minimum impact to the built environment.


  • To share experience, knowledge, and skills between academia and industry in relation to the domain of ‘resilient built environments’
  • To conduct a scoping study and develop a roadmap to identify opportunities to integrate and embed resiliency into building management systems and smart home systems
  • To map existing state-of-the-art IoT data-driven anomaly detection techniques developed within GCHQ project in BRE to understand generalisability, strength, and weaknesses of the IoT based cyber-attack and abnormal behaviour/anomaly detection within built environments
  • To support Cube Control and BRE to formulate, structure, and develop their future innovation agendas around building management systems and smart homes
  • To develop a programme of research around resilient built environments
  • To provide industry exposure to four PhD students involved in this project and help them understand how to effectively collaborate and organise their research contributions
  • To develop long-term collaboration between user partners and develop a consortium of interested stakeholders (Cardiff University, GCHQ, Cube Control, Building Research Establishment) in the domain of resilient built environments.

This project is developed around the GCHQ National Resilience Fellowship awarded to the principal investigator.

Academic team

Dr Charith Perera

This project is funded by the Engineering and Physical Sciences Research Council’sPETRAS Centre of Excellence for IoT Systems Cybersecurity, through UCL.

This project aims to clarify the disruptive principle of legal liability in multi-agency societies (UK and Japan), and propose relevant legal policy to establish the rule of law in the age of artificial intelligence (AI), that enables the construction of the “NAJIMI society” where humans and intelligent machines can cohabit with sensitivity to cultural diversity. The project will contribute to making UK and Japanese society more adoptive to emerging technology through clarifying the legislation.

Objectives of this project

  • Establish the distributive principles of legal liability for accidents involving cooperation between a human and intelligent machine where human subjectivity may be influenced by the autonomous behaviour of the machine
  • Proposition of the legal policy to establish the rule of law in the age of AI
  • Examination of the validity of multi-dimensional dynamic game theory to capture and analyse situations where humans and intelligent machines interact
  • Study the attribution of blame and responsibility in autonomous driving scenarios with varying levels of AI involvement and explainability
  • Study the measurement of human trust and assessment of reliability in autonomous vehicles
  • Establish the theoretical background of subjectivity in multi-agent situations and implement a psychological experiment on trustworthiness of machines in collaborative tasks
  • Comparison of the output of the same psychological experiments on subjectivity during human-intelligent machine interaction in the UK and Japan
  • Engagement in comparative fieldwork on human-robot relations in the UK and Japan to better account for cultural variability of agency in different social, legal, and scientific contexts.

Collaborative research groups

To achieve the project’s objectives, three collaborative research groups have been established:

  • Law-Economics-Philosophy group: propose the stylised model to analyse and evaluate the multi-agent situation to establish the disruptive principle of legal liability and the legal policy for the rule of law in the age of AI
  • Cognitive Robotics and Human Factors and Cognitive Psychology group: implement computer simulations and psychological experiments to capture data on human interaction and performance as well as attitudes and experiences of intelligent machine i.e. autonomous vehicles
  • Cultural Anthropology group: engage in comparative fieldwork on human-robot relation in the UK and Japan to better account for cultural variability of distributed agency within different social, legal, and scientific contexts.

The UK and Japan share similar principles in categorising legal liability, which historically and philosophically attribute liability to human agents imagined as autonomous and independent. Recent developments in AI that give autonomy to artificial agents e.g. autonomous driving systems, social robots, intelligent surgery/diagnosis, challenges traditional agency and presents problems in determining legal liability within multi-agency societies. Based on current legislation, it is difficult to distribute legal liability in scenarios where an accident occurs between a human and intelligent machine.

Although legal theory assumes that the human should take responsibility for the accident, human subjectivity is influenced by the behaviour of intelligent machines in human-intelligent machine interaction. The lack of clear disruptive principles of legal liability may negatively impact the development of multi-agent societies as, without workable legal liability in place, there is limited trust in the behaviour and quality of the intelligent machinery that may cause injury.

Academic team

Professor Phil Morgan
Professor Dylan Jones OBE
Associate Professor Tatsuhiko Inatani
Professor Minoru Asada
Associate Professor Hirofumi Katsuno
Assistant Professor Kentaro Asai
Associate Professor Kazuya Matsuura
Assistant Professor Yuji Kawai
Professor Jun Tani
Associate Professor Takako Yoshida
Hayato Tanaka (PhD student)
Visiting Scholar Daniel White

This project is funded by the Economic & Social Research Council.

This project aims to examine how the COVID-19 response in Peru is impacting on nutritional risks of mothers and infants in the short, medium and long term compared to pre-COVID assessments in the same communities. We work with national, regional and local stakeholders through co-creation of short-term and longer-term mitigation strategies to readapt health services for maternal and child nutrition in Peru.


The project’s specific objectives are:

  • To assess the impact of COVID-19 on exclusive breastfeeding, continued breastfeeding and complementary feeding practices in relation to nutritional risks of infants
  • To assess reductions in iron supplementation in the context of the new strategies implemented since the pandemic began
  • To examine the impact of COVID-19 on household food security, maternal psychological wellbeing, changing quality of diet and healthy/unhealthy dietary indicators in relation to nutritional risks in adults of overnutrition and noncommunicable diseases
  • To determine how household dietary practices and behaviours adapt and respond to the COVID-19 pandemic
  • To co-create support systems for design or delivery of methods for nutritional counselling, growth monitoring, iron supplementation for infants and young children using remote technologies or socially distanced health services.

Prior to COVID-19, Peru was world-leading in reducing malnutrition through intersectoral actions for infant and young child feeding and delivery of health services to disadvantaged sectors. Estimates of the indirect effects of COVID-19 on maternal and child mortality highlight increased deaths due to the disruption of health systems and decreased access to food.

Academic team

Dr Emily Rousham
Dr Nervo Verdezoto Días
Professor Paula Griffiths
Dr Rebecca Pradeilles
Hilary Creed-Kanashiro
Rossina Pareja

This project is funded by the Engineering and Physical Sciences Research Council.

This project aims to understand the risks and challenges surrounding workplace Trust, Identity, Privacy and Security (TIPS) as a result of home working practices throughout COVID-19. We will explore and identify these issues taking a socio-technical approach, focusing on small and large organisations.

Our goal

To provide key, novel insights into the new challenges and tensions in relation to TIPS in these environments and provide the much-needed foundation for approaches to address these issues.

As a result of the COVID-19 pandemic, many workplaces had to suddenly transition to remote working, despite a lack of training, remote-working policies, or in some cases, work devices. With the added pressures of working from home (e.g., childcare, impaired work-life balance), this new way of working has changed the risks and challenges surrounding workplace TIPS. This is exacerbated even further with the increase in cyberattacks specifically targeting remote workers.

Academic team

Dr Emily Collins
Dr John Blythe
Ben Koppelman
Dr Jason Nurse
Professor Niki Panteli
Dr Nikki Williams

This project is funded by SPRITE+ through the Engineering and Physical Sciences Research Council.

This project aims to develop a self-sustaining hub of expertise to support the foundation industries’ (cement, ceramics, chemicals, glass, metals, and paper) transformation into non-polluting, resource efficient modern competitive manufactories working in harmony with the communities in which they are situated.


  • Transferring best practice – applying Gentani (minimum resource needed to carry out a process)

Across the foundation industries, there are many similar processes. Using the philosophy of Gentani, this research benchmarks and identifies best practices considering resource efficiencies and environmental impacts across sectors and shares information horizontally.

  • “Where there’s muck there’s brass”

Creating new materials and process opportunities. The development of smart, new materials and processes that enable cheaper, lower-energy and lower-carbon products is key to transforming our foundation industries. There is great potential to add more value by “upcycling” waste by further processes to develop new materials and alternative by-products from innovative processing technologies with less environmental impact.

  • Working with communities

Co-development of new business and social enterprises. Lots of warm air and water are produced across the sectors, providing opportunities for low grade energy capture. Working collaboratively with communities around foundation industries, the potential for co-located initiatives will be identified (e.g., district heating, market gardening etc.)

TransFIRe is a consortium of 12 institutions, 49 companies, and 14 NGO and government organisations related to the sectors. Expertise spans the foundation industries as well as energy mapping, life cycle and sustainability, industrial symbiosis, computer science, AI and digital manufacturing, management, social science, and technology transfer.

Academic team

Professor Mark Jolly
Professor Konstantinos Salonitis
Dr Graham Ormondroyd
Clive John Mitchell
Dr Evangelia Petravratzi
Dr Jonathan Cullen
Professor Rossi Setchi
Professor Sam Evans
Professor Sue Black
Professor Steven Yearley
Professor Shaowei Zhang
Professor Phil Purnell
Professor Justin Perry
Dr Matthew Unthank
Professor Paul Bingham
Professor Peter Ball
Dr Steve Cinderby
Dr Gary Haq
Tom Bide
Dr Anne Velenturf

This project is funded by the Engineering and Physical Sciences Research Council.

This project uses home-based Internet of Things (IoT) technology and cyber-enabled crime to explore the relationship between the difference in the adoption and use of new technology, and the exploitation of these technologies for criminal purposes.

Main objectives of the project

  • Use home-based IoT technology as a framework to see how exploitable they are for use in cyber crimes
  • Investigate the influence of differences in psychological characteristics and socio-demographic factors (e.g. risk, impulsivity, age, gender, education) on the adoption and use of IoT devices
  • Examine how the individual differences in adoption and use may contribute to the exploitation of IoT devices.

By addressing these objectives, further understanding of the relationship between technology, potential victims, and malicious actors can be built. The Internet of Things has increased the number of connected devices in the home with new technology able to connect to the internet and other devices. From smart locks and home surveillance to connected appliances, lighting, and heating systems, this technology has many advantages for saving money, time, and energy.

Such technology also presents risks to both data and personal security due to potential exploitation of these devices during forms of crime such as burglary, extortion, harassment, and abuse. Understanding is needed on the factors that may influence the adoption and use of smart home technologies and how these may contribute to, or mitigate, potential risks.

Academic team

Dr Emma Williams
Professor Phil Morgan
Dr Emma Slade
Dr Duncan Hodges
Professor Dylan Jones OBE

This project is funded by the Economic & Social Research Council Centre for Research and Evidence on Security Threats.

This project aims to explore how augmented reality technology can be used to make important information about surroundings accessible to people with low vision by means of visual enhancements.

The project will explore the suitability and effectiveness of an augmented reality technology as a future low vision mobility aid for people with low vision. It is hoped that highlighting the hazards in real-time will help people with their mobility and wayfinding. Providing contextual information about the environment in real-time will enable people to experience greater independence.

The project will result in a high-tech, augmented reality prototype device designed to help people with low vision with their mobility problems. It will also capture data on usability and mobility metrics. The findings of this research will be published in a peer reviewed journal so that others may benefit from it.

Academic team

Dr Parisa Eslambolchilar
Professor Yukun Lai
Professor Tom Margrain
Hein Htike (PhD student)

This project is funded by The Guide Dogs for the Blind Association.