Horizon TAPs attending ACM CHI 2022


The ACM CHI Conference on Human Factors in Computing Systems is the premier international conference of Human-Computer Interaction (HCI). CHI – pronounced ‘kai’ – annually brings together researchers and practitioners from all over the world and from diverse cultures, backgrounds, and positionalities, who have as an overarching goal to make the world a better place with interactive digital technologies.

CHI 2022 is structured as a Hybrid-Onsite full conference which runs from April 30–May 5 in New Orleans, LA.

Two Horizon Transitional Assistant Professors will be presenting their work at CHI 2022.

Horia Maior: Moving from Brain-Computer Interaction to Personal Cognitive Informatics.

Consumer neurotechnology (a method or device in which electronics interface with the nervous system to monitor or modulate neural activity) has arriving even as algorithms for user state estimation are still being actively defined and developed. Consumable wearables that aim to estimate cognitive changes from wrist data or body movement are now readily available.  But does this data help people? It’s now a critical time to address how users could be informed by wearable neurotechnology, in a way that’s relevant to their needs and serves their personal well-being. This special interest group will bring together the key HCI communities needed to investigate this topic: personal informatics, digital health and wellbeing, neuroergonomics, and neuroethics.

In addition, Horia also presented: The Impact of Motion Scaling and Haptic Guidance on Operator’s Workload and Performance in Teleoperation.

Neelima Sailaja: Where lots of people are sharing one thing, as soon as one person does something slightly different it can impact everyone: A Formative Exploration of User Challenges and Expectations around Sharing of Accounts Online.

Users often share their accounts with others; however most accounts support only single user interactions. Within industry, Netflix and Disney+ providing profiles within accounts are evidence that popular services are identifying and responding to user needs in this context, however the solutions here are mostly naïve. Within academia, while sharing of practices are of interest, the practicalities of dealing with them are yet to be studied.  Neelima’s paper highlights the said gap in research and presents preliminary findings from a series of focus groups that revealed practical challenges and future expectations around the experience of sharing, social implications and user privacy. Research in this area will continue by integrating these findings with expert interviews – held with ‘makers’ who research and work on such technologies. The outcome will be a set of holistic design recommendations that form a practical guide for support around account sharing.



Congratulations to Horia Maior

Earlier on in the week Horizon Transitional Assistant Professor, Horia Maior, was named by the Foundation for Science and Technology as one of their 2002 Future Leaders.

Horia explained:

“I am very excited about joining the Future Leaders 2022 cohort. The Foundation Future Leaders programme brings together a cohort of around 30 mid-career professionals over the course of a year, with approximately 10 representatives each from the research community, industry, and the civil service and wider public sector. Over a 12-month period, the group meet and discuss with senior figures from government, parliament, universities, large industry, SMEs, research charities and others (more information here https://www.foundation.org.uk/Future-Leaders/Foundation-Future-Leaders-2022).

During my research career I have acquired a good understanding of how research and innovation are used in academia, and the challenges the sector is facing in a rapidly changing world. The Future Leaders program is an excellent opportunity for me to make links and understand how science, research and innovation are used not only in academia, but also in other sectors, including the government, wider public sector, and industry; and how a diverse range of stakeholders can support and enrich policy development.

I see the opportunity provided by the Foundation of Future Leaders program as a platform to generate an ongoing, open dialog with a group of people from diverse backgrounds and experiences, including government, industry, and academia. I will make use of meetings, drop-in sessions and conference time offered through the Foundation of Future Leaders program to lead pin-point discussions that will address research challenges within academia in general, as well as in-depth discussions about some of our ongoing  work in Horizon, the Cobot Maker Space and the Trustworthy Autonomous Systems Hub at the University of Nottingham.

I am very excited to join and engage in discussions led by other researchers, industry practitioners, civil servants, parliamentary members and members of the wider public sector. I will try to be active in writing and publishing blogs and social media posts about the events and ongoing discussions. Moving forwards beyond this program, I would like to build a network of trusted colleagues through the programme and maintain an active link that will facilitate knowledge exchange and impact across multiple sectors.”


Helena updates us on her latest research




As a socio-technical researcher I work on projects that combine elements of computer science and the social sciences. I focus on bringing in the human experience and perspective into our understanding of technology and enjoy highlighting how these human factors can positively shape technological development. Joining Horizon as a Transitional Assistant Professor allows me space to develop my research portfolio and I am excited to be bringing this approach into a new research collaboration, called “Artificial Intelligence Decision Support for Kidney Transplantation (AID-KT)”

AID-KT is funded by NIHR and is led by a team at the University of Oxford. The project co-leaders are Simon Knight in the Centre for Evidence in Transplantation and Tingting Zhu from the Oxford Computational Health Informatics Lab. The project seeks to improve outcomes in kidney transplantation by developing an AI decision support tool.

The kidney is the most transplanted organ – accounting for just over 65% of organ transplants. At any one time, there are around 5,000 patients on the waiting list for a kidney transplant in the UK. However, donor organs are often turned down due to fears of poor outcomes for patients. Currently there is an absence of support tools to help clinicians determine and discuss with their patients how likely the transplant of a specific donor kidney will be for them, plus how this might compare to not having the transplant and waiting for another kidney to become available. Being able to predict the graft survival of the kidney after transplant could greatly increase the transplant success rate, leading to better outcomes for, and making better use of the available organ pool and healthcare resources.

The aim of this project is to address this absence by developing and testing a clinical decision support tool for kidney transplant. It will be driven by machine learning techniques and will help answer this crucial clinical question for potential kidney donor recipients:

Will my outcome be better if I accept this transplant offer, or wait for the next offer in the future?

Much of the project focuses on the creation and validation of machine learning models that can accurately predict graft and patient survival following transplant and patient outcomes if a transplant offer is declined. Alongside this, we are conducting work to make these models explainable and transparent. Little existing research has investigated how to present these kinds of clinical predictions to patients and clinicians in ways they find accessible. Therefore, we will be involving clinicians and patients in our research – through qualitative interviews and other methods – to assess which data are useful to them and how data should be presented to support decision making and informed consent. As part of this we recognise that patients will differ in terms of the level of detail they want to have and the extent to which they prefer to lead their own decision making or defer to clinical judgement. As such, the clinical decision tool needs to be adaptable to the preferences of different individuals. In addition, it also needs to make its salient features visible and interpretable to clinician users so that they can understand how the model is using underlying data and explain the predictions made to patients clearly. By bringing in these human perspectives to the development of the tool we can optimise its usefulness and effectiveness in clinical settings. By extension we can also, hopefully, improve acceptance rates for kidney transplants as well as post-transplant outcomes.

Written by Helena Webb



Horizon TAPs

A key feature of Horizon is our transitional fellowship scheme – this recruits highly talented research fellows into the academic career track, providing time and space initially to allow a greater focus on developing their research portfolio and leadership skills. This mechanism also permanently embeds the practices of cross-disciplinary digital economy working into key academic units throughout the university of Nottingham. 

Find out more about the research interests of our current TAPs

Our new TAPs

We are delighted to announce our new Transitional Assistant Professors:

Georgiana  Nica-Avram

Horia Maior

Helena Webb

Neelima Sailaja


Stuart Reeves – disseminating research on voice interfaces to UX and design practitioners

This is a short story about how our team—myself, Martin Porcheron, and Joel Fischer —disseminated our research on voice interfaces to UX and design practitioners through a varied campaign spanning over a year and a half to the present.

It began with a technology field trial that formed part of Martins PhD, during which he collected many hours of audio recordings of Amazon Echo use in domestic settings where the devices were deployed for a month. While working towards our first major academic milestone — a CHI 2018 paper (which was submitted in September 2017), we also began discussing and presenting early versions of this work-in-progress with practitioners.

This engagement with practice grew from exchanges with the BBC UX&D design research team with whom we discussed our emerging research and its results. Subsequently this led to us conducting a BBC UX&D “Studio Day” workshop that enabled us to do a more focussed presentation, coupled with a practical exercise for groups of UX&D practitioners, to consider issues raised when designing for voice interfaces. Performing this mini-workshop helped engender a more meaningful discussion than simply presenting what were then very preliminary results.

We presented our work publicly to the Cambridge Usability Group (CUG), and to a UX agency in London. Both activities led us to consider taking the material to a larger conference.

To begin with, these initial engagements with smaller audiences of practitioners enabled us to gauge what might be interesting and relevant for them, as well as providing us with a better sense of what kind of involvement with voice interfaces was realistic for designers. They also enabled us to gradually ‘prototype’ our ideas and presentational formats in a way that integrated our (ongoing) work, allowing us to establish a ‘feedback’ between the research side of things (e.g., developing papers) and practitioner-facing talks.

With our CHI 2018 paper accepted, I then presented our work to Interaction18, a large interaction design industry conference organised by the Interaction Design Association (IxDA). The tight 15 minute slot offered by IxDA required significant sharpening in order to maximise our work’s relevance and impact. My talk at Interaction18 was recorded and made more widely available by the conference organisers. I also decided to transform it into a Medium post which I made available soon after. This resulted in a positive uptake, 1.6k+ views on Medium and counting.

Presenting at a reasonably high-profile event for UX and design practitioners let us establish a formula—in miniature— that we could be confident with, that mostly seemed to ‘work’ for people and be of relevance – as evidenced by in-person feedback and further enquiries afterwards. Critically, it also generated further interest from practitioners in the form of invitations to speak about our work at other venues. In this way, smaller UX conferences and meetups followed and have built on this: The Research Thing, London in April; HCID Open Day at City, University of London in May; The Design Exchange, Nottingham in August; and the Service Design Meetup, London in October.

Whilst not clear as to what all this ultimately will lead to, we have a number of other future events and publications in development. It proves difficult to track and trace our impact on UX and design practitioner communities, even though we can capture how our learning as academics that engaging with practice has helped shape the research in various positive ways: increased conceptual clarity, focus, and a better appreciation for the value of different formats. All of these in turn help sharpen our standard academic dissemination and research approach.



Photo by Leo Cardelli from Pexels

James Pinchin: “I’ve very much enjoyed supervising Kyle Harrington throughout his studies investigating human search behaviour in emergency situations in order to facilitate the development of safer walking technologies for vulnerable people. Co-supervised by Prof. Sarah Sharples, Kyle is based within the Human Factors Research Group and Horizon Digital Economy Research.  Kyle’s research was sponsored by Phillips Research”.

A Socio-Technical approach to missing incidents

Every year the police receive around a quarter of a million reports of missing people in England and Wales alone. Whilst the vast majority of those who become missing return home safely; people with additional care and support needs are far more likely to suffer from physical, emotional or psychological harm. Missing Incidents are not only traumatic for those involved, but are also likely to contribute to overall public spending; both with respect to the resources required for Missing Person searches, but also due to the increased likelihood of the breakdown of familial care following difficult to manage behaviours. Effective responses to these incidents are imperative, but there is little academic research which explores how these practices could be improved and no work at all investigating the decision-making of carers or parents during these incidents.

In his recently submitted thesis, Kyle Harrington draws together several disparate research areas, alongside original research, which helps to elucidate how those responsible for a person with care and support needs search, navigate and make decisions under stress. The work described in his thesis represents an attempt at a systematic understanding of how missing incidents unfold, how decision-making within missing incidents can be predicated, and ultimately what can be done to address the problem. With a focus on decision-making and technology; the thesis uses a three stage approach to describe, predict and address the problem of Missing Incidents. Several key design recommendations were produced which are intended to inform the design of new technologies for supporting missing person searches and may be of use to technology developers, policy-makers, care providers and other stakeholders

The Royal College of Physicians, safe medical staffing report and the relevance of mathematical sciences in real-world challenges.

On Friday 13th of July, the Royal College of Physicians (RCP), a British professional body dedicated to improving the practice of medicine, is due to release the safe medical staffing report, a comprehensive set of guidelines to improve current working standards and staffing within hospitals. It is now easily observable how secondary healthcare systems, both within the UK and abroad, are under increasing pressure. This is mostly due to growing patient admissions and a decline in available beds, along with an increase in the complexity of conditions and their necessary treatments. Arguably, healthcare systems must undergo major changes and optimise the use of limited (often human) resources, and the RCP seems to be in strong agreement with this interpretation of the current situation. Its large body of physicians and professionals has long been working in order to make positive contributions, helping to ease the working conditions of medical staff and improve the experiences of patients across this country.

On this occasion, the soon to be published staffing report will feature contributions borrowed from the extensive research of an interdisciplinary academic group of engineers, doctors, human factor researches and mathematicians within the University of Nottingham (see https://wayward.wp.horizon.ac.uk/). I have myself had the privilege of being part of this great team during the last 2 years. As a mathematician, I must confess this has been challenging at times; especially, when navigating through rooms full of clinicians, nurses and various stakeholders, trying to make sense of the important real-world challenges they face during their everyday life. In addition to that, I have experienced at several times how these professionals, with their different backgrounds, interests and opinions, often find it hard to grasp the exact nature of the work that a bunch of statisticians and scientists of the sort can do, and how it is we can contribute to very topical matters such as this one. If we don’t make a good job of communicating our work, we risk facing scepticism and marginalization.

 Thus, I would like to bring your attention to the fact that, the soon to be released RCP staffing report directly features outputs and key insights offered by statistical tools in the domains of queueing theory, Bayesian inference and Markov chain Monte Carlo, just to name a few. Luckily, there is no real reason why you should go on to Google these keywords; at times, it is up to us to abstract you from the technicalities and complex concepts, and put the focus on informative key findings that bring something to the table. Hence, I thought I would provide a few of the insights that came out of our data analyses and discussions with the various great teams at the Nottingham University Hospitals NHS Trust. The results here are only representative of the hospitals analysed, and data used was gathered during a 4 year time-span, from two major university hospitals jointly providing secondary healthcare to over 2.5 million residents in the United Kingdom. At the end of the post, you will find a list of references to some engineering, statistics and computer science publications that offer a rather comprehensive look at the (exciting!) mathematics lying at the heart of this work.

Have a look at the two figures above – you will find a bunch of colourful graphs showing what are seemingly temporal patterns distributed across various medical disciplines. The technical name to these is “Bayesian posterior credible intervals” – on a basic level, this is simply Bayesian analogue to a confidence interval, a.k.a. our favourite concept in that dreaded Year-1 statistics class. These ones reflect variations on average patterns of task demand in the hospitals, both weekly and year-round. Most importantly, these are not descriptive results, i.e. they don’t just average data here and there, nor are they built on strong assumptions common in practical low-level models. These results are extracted from a model of high complexity accounting for day-to-day dependence, random noise, distribution of observations … and the outputs reflect uncertainty regarding our confidence in the scales. So, why is this important? Why did the RCP or other physicians care? After all, they are nothing but confidence intervals, they tell us nothing for sure!

And that is precisely the point here. Patient arrivals, task demands, discharges, treatment times … these are all subject to such great noise. Ultimately, day-to-day work-demand within hospitals is, to a good extent, fairly unpredictable. As a consequence, every individual builds an (often very biased) opinion on the requirements, demands and plan of action necessary, usually based on their personal experiences. Hence, they have no means to factor for objective measures of certainty regarding what is predictable, and to what extent. In addition, they are good doctors, who devote their time to gain the skills that can ensure puts us on good hands; it is only to be expected that they have no expertise on designing the advanced mathematical frameworks that can offer an overview on workload, that is free of (most) sources of bias.

[1] Perez, I., Hodge, D., & Kypraios, T. (2017). Auxiliary variables for Bayesian inference in multi-class queueing networks. Statistics and Computing, 1-14

[2] Perez, I., Pinchin, J., Brown, M., Blum, J., & Sharples, S. (2016). Unsupervised labelling of sequential data for location identification in indoor environments. Expert Systems with Applications, 61, 386-393.

[3] Perez, I., Brown, M., Pinchin, J., Martindale, S., Sharples, S., Shaw, D., & Blakey, J. (2016). Out of hours workload management: Bayesian inference for decision support in secondary care. Artificial intelligence in medicine, 73, 34-44.