Publications

Human extra-vehicular activity (EVA) plays a vital role in current and near future space exploration for two reasons: the superior dexterity exhibited by human astronauts, and their flexible problem-solving and decision-making capabilities. However, the dexterity of astronauts during EVA is limited by the flexibility and tactility of their EVA suit gloves, which are primarily designed to provide thermal insulation and pressure for the hand. This creates a compromise between utility and protection. To address this compromise, a Passively Actuated Short-range Telehaptic (PAST) device is proposed. The PAST device couples the motion of fingers between a robotic hand and a human hand through a hydraulically actuated linkage. It also transfers tactile information, including pressure, direction of motion, and position of contact, via a taxel array. Results demonstrate that the proposed prototype PAST device surpasses an unpressurised benchmark heavy work glove(HWG) in tasks involving tactile position and motion direction identification. This provides evidence supporting the feasibility of enhancing astronaut dexterity during EVA through the use of PAST devices as an alternative paradigm to gloves.

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Journal article

Chen L, Xiao S, Chen Y, Sun L, Childs PRN, Han Jet al., 2025,

An artificial intelligence approach for interpreting creative combinational designs

, Journal of Engineering Design, Vol: 36, Pages: 920-947, ISSN: 0954-4828

Combinational creativity, a form of creativity involving the blending of familiar ideas, is pivotal in design innovation. While most research focuses on how combinational creativity in design is achieved through blending elements, this study focuses on the computational interpretation, specifically identifying the ‘base’ and ‘additive’ components that constitute a creative design. To achieve this goal, the authors propose a heuristic algorithm integrating computer vision and natural language processing technologies, and implement multiple approaches based on both discriminative and generative artificial intelligence architectures. A comprehensive evaluation was conducted on a dataset created for studying combinational creativity. Among the implementations of the proposed algorithm, the most effective approach demonstrated a high accuracy in interpretation, achieving 87.5% for identifying ‘base’ and 80% for ‘additive’. We conduct a modular analysis and an ablation experiment to assess the performance of each part in our implementations. Additionally, the study includes an analysis of error cases and bottleneck issues, providing critical insights into the limitations and challenges inherent in the computational interpretation of creative designs.

Journal article

Caspe F, Shier J, Sandler M, Saitis C, McPherson Aet al., 2025,

Designing neural synthesizers for low-latency interaction

, AES: Journal of the Audio Engineering Society, Vol: 73, ISSN: 1549-4950

Neural audio synthesis (NAS) models offer interactive musical control over high-quality, expressive audio generators. While these models can operate in real time, they often suffer from high latency, making them unsuitable for intimate musical interaction. The impact of architectural choices in deep learning models on audio latency remains largely unexplored in the NAS literature. In this work, the authors investigate the sources of latency and jitter typically found in interactive NAS models. They then apply this analysis to the task of timbre transfer using the RAVE model (Realtime Audio Variational autoEncoder), a convolutional variational autoencoder for audio waveforms introduced by Caillon and Esling in 2021. Finally, an iterative design approach for optimizing latency is presented. This culminates with a model the authors call BRAVE (Bravely Realtime Audio Variational autoEncoder), which is low-latency and exhibits better pitch and loudness replication while showing timbre modification capabilities similar to RAVE. It is implemented in a specialized inference framework for low-latency, real-time inference, and a proof-of-concept audio plugin compatible with audio signals from musical instruments is presented. The authors expect the challenges and guidelines described in this document to support NAS researchers in designing models for low-latency inference from the ground up, enriching the landscape of possibilities for musicians.

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Journal article

Demirel P, Kesidou E, Gamze Ozturk D, 2025,

IT-enabled organisational transformation and green employment growth in microfirms

, Business Strategy and the Environment, Vol: 34, Pages: 5031-5058, ISSN: 0964-4733

In this paper, we explore whether IT-enabled organisational transformation (ITOT) moderates the relationship between eco-innovation and the growth performance of microfirms. Our framework conceptualises ITOT in microfirms as a multistage process that includes: (i) setting a digitalisation strategy, (ii) adopting advanced information systems technology (IST) artefacts and (iii) developing in-house digital resources and capabilities. The analysis of a sample of 5015 microfirms from 39 countries indicates that eco-innovations boost firm growth when coupled with (i) a formalised digitalisation strategy, (ii) adoption of advanced IST artefacts (e.g., digital technologies that characterise Industry 4.0) and (iii) digital resources and capabilities in microfirms. These findings contribute to the growing digitalisation literature by highlighting the essential role that ITOT processes play in enabling sustainability-led growth pathways for microfirms. The paper advocates for the viability and performance benefits of a twin digital and ecological transformation and showcases the potential of ITOT for an economically successful net-zero transition that embraces microfirms.

Journal article

Deady M, Collins DAJ, Glozier N, Gardiner E, Arena A, Gayed A, Bryant R, Calvo RA, Harvey SBet al., 2025,

Naturalistic evaluation of HeadGear: a smartphone app to reduce depressive symptoms in workers

, Behavior Therapy, Vol: 56, Pages: 529-542, ISSN: 0005-7894

Mobile health (mHealth) apps have the potential to expand access to evidence-based interventions for mental health conditions, including depression. HeadGear was developed to prevent depression and improve well-being among the working population and was associated with significant positive effects in an efficacy trial. This study presents the results from a naturalistic trial intended to evaluate real-world usage of the app. We examined the naturalistic use of HeadGear between March 2019 and March 2022, using app analytic data, in-app event data, and surveys assessing depressive symptoms, well-being, and work performance repeated at 30-day intervals over 5-month app usage. During the observation period, HeadGear was widely disseminated to the public, and downloaded 26,455 times. Of those who downloaded the app, 12,995 completed baseline. The mean age of users was 38.23 (SD = 12.39) and 60% were women. Approximately one in four met criteria for probable depression at baseline. Depressive symptoms showed consistent improvement at all time points (Cohen’s d ranging from 0.24 at 1 month to 0.13 at 5 months). A similar pattern emerged for well-being. Work performance showed improvement to 2-month follow-up only. The strongest change was found for those with greater symptom severity at baseline, and those with high app engagement. Attrition at follow-up points was high. Findings regarding the real-world use of HeadGear are promising and highlight the use of such apps among those with higher symptom severity (despite the intended use of the app as a prevention tool). Further work is required to tailor mHealth apps to reach their full potential through an enhanced understanding of the utility of individual features for effectiveness and engagement.

Journal article

Ikeya K, Guerrero-Gonzalez FJ, Kiewiet L, Cardin M-A, Cilliers J, Starr S, Hadler Ket al., 2025,

Hybrid lunar ISRU plant: A comparative analysis with carbothermal reduction and water extraction

, ACTA ASTRONAUTICA, Vol: 230, Pages: 148-168, ISSN: 0094-5765

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Citations: 2

Journal article

Moreschini A, Astolfi A, 2025,

Closed-Loop Interpolation by Moment Matching for Linear and Nonlinear Systems

, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 70, Pages: 2918-2933, ISSN: 0018-9286

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Citations: 1

Journal article

Frade JLH, Giraldi JDME, Porat T, 2025,

The country-of-origin effect on vaccination: a systematic literature review and research agenda

, Management Review Quarterly, ISSN: 2198-1639

The COVID-19 pandemic raised awareness and concerns regarding the country-of-origin of vaccines. During this period, we witnessed the emergence of a country-of-origin effect in vaccination perceptions. The country-of-origin effect is a well-documented marketing phenomenon where the origin country of a product influences consumer decisions, brand associations, and evaluations. To investigate this phenomenon, a systematic literature review was conducted using Scopus database, employing a diverse array of search terms. The review identified 52 articles that examined the country-of-origin effect on vaccination. These studies fall under different subject fields, such as Medicine and Social Science, and were published across 39 different journals, confirming the interdisciplinary nature of the topic. Moreover, the studies covered 48 countries, with some being multicultural. The results reveal the presence of a national bias, a preference for Western vaccines, distrust towards Chinese and Russian vaccines, and the impact of demographic factors, such as gender, age, and income. The national bias was observed across at least 17 countries, such as USA, China, UK, Germany, Turkey and Iran. It persists even in countries without early COVID-19 vaccine development (e.g., Brazil, Ghana, Japan, South Korea, Spain and Taiwan). The preference for Western vaccines and distrust towards Chinese and Russian vaccines was observed across diverse regions including Europe (e.g., France), Latin American (e.g., Brazil), Eastern Europe (e.g., Hungary), the Middle East (e.g., Turkey, Israel), and Asia (e.g., Japan). The authors discuss potential underlying reasons, implications for policy makers and health management, and propose a comprehensive agenda for future research, including the role of politics, media, endorsements, and other vaccines and medications.

Journal article

Ballou N, Hakman T, Vuorre M, Magnusson K, Przybylski AKet al., 2025,

How do video games affect mental health? A narrative review of 13 proposed mechanisms

, Technology, Mind, and Behavior, Vol: 6, Pages: 123-143, ISSN: 2689-0208

Researchers have proposed a variety of mechanisms through which playing video games might affect mental health by displacing more psychosocially beneficial activities, satisfying or frustrating basic psychological needs, relieving stress, and many more. However, these mechanisms and their underlying causal structures are rarely made explicit. Here, we review 13 proposed effects of gaming on mental health. For each, we specify a counterfactual—that is, what concrete aspect of gaming should be changed in a hypothetical alternative universe to produce the effect of interest—and illustrate these with example directed acyclic graphs. In doing so, we hope to encourage more focused efforts to propose, falsify, and iterate on (causal) theories using well-established formal methods of causal inference. Only in doing so can the field realize its potential to inform clinical interventions, regulation, game design, and the behavior of players and parents.

Conference paper

Yurman P, Malpass M, Balaam M, Zheng CY, Luft Y, Mougenot C, Lupetti MLet al., 2025,

Maternal Machines: Imagining Experiences in Perinatal Care

Perinatal care is a term that broadly refers to the period of time from pregnancy up to a year after giving birth. Imaginaries, fictional scenarios, patents and actual designs to support affected stakeholders during this period reflect how this topic has for a long time fed into society’s dreams, fears and desires about care. Smart monitors of infants’ sleep, respiration, heart rate or temperature, cots with facial recognition, swing chairs that are ‘Alexa compatible’, chatbots for postpartum depression, ‘maternal’ Alexas or nanny robots are examples of the potentials that this topic offers for imagining scenarios for care and wellbeing. Often rich with insights about societal dreams, fears and desires about what we would like technologies to do for us, imagined scenarios can also indicate ways in which we regard those already engaged in roles of care, echoing cultural and gendered tropes. As AI and related technologies increasingly become entangled in situations of care, the imagined possibilities in contexts of such complex, sensitive and emotionally charged spaces are worth examining, whilst interrogating how HCI technologies in perinatal care could expand beyond quantifiable data and tap into sensorial, non-numerical forms of knowledge. In this workshop, we will look at ideated scenarios with technologies related to maternal and infant care in contemporary, historical and cultural contexts including those from Japan, and we will create our own imagined scenarios of care. Through a mixture of activities that include presentations, drawing, hands-on interactions and group conversations we will discuss opportunities and implications in the design of technologies for maternal/parental and infant care around the perinatal period. Our imagined scenarios will explore in particular two interrelated themes in the research: non-numerical forms of knowledge and touch.

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Conference paper

Chen L, Cheang W, Jiang Z, Xu Y, Cai Z, Sun L, Childs P, Han J, Hansen P, Zuo Het al., 2025,

I-Card: a generative AI-supported intelligent design method card deck

, 2025 Conference on Human Factors in Computing Systems-CHI, Publisher: Association for Computing Machinery, Pages: 1-22

A design method card deck helps designers understand and provoke thinking by presenting each method in a simple format and allow designers to switch between methods seamlessly by maintaining the same simple format across the deck. However, recent observations have shown designers hesitate to use a card deck due to the lack of support, while other tools have provided identified support with generative AI. Through a formative study, we identified the specific support designers need when applying the design method cards and intentions in integrating generative AI. Accordingly, we developed the intelligent design method card deck, I-Card, which integrates generative AI to provide applicable design methods, design knowledge and data support, and interactive and dynamic support. A user study demonstrates that I-Card improved the design efficiency and applicability by offering personalized guidance, enhanced decision-making with comprehensive data generation and provided more design inspiration via interactive support.

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Journal article

Arana-Catania M, Sonee A, Khan A-M, Fatehi K, Tang Y, Jin B, Soligo A, Boyle D, Calinescu R, Yadav P, Ahmadi H, Tsourdos A, Guo W, Russo Aet al., 2025,

Explainable reinforcement and causal learning for improving trust to 6G stakeholders

, IEEE Open Journal of the Communications Society, Vol: 6, Pages: 4101-4125, ISSN: 2644-125X

Future telecommunications will increasingly integrate AI capabilities into network infrastructures to deliver seamless and harmonized services closer to end-users. However, this progress also raises significant trust and safety concerns. The machine learning systems orchestrating these advanced services will widely rely on deep reinforcement learning (DRL) to process multi-modal requirements datasets and make semantically modulated decisions, introducing three major challenges: (1) First, we acknowledge that most explainable AI research is stakeholder-agnostic while, in reality, the explanations must cater for diverse telecommunications stakeholders, including network service providers, legal authorities, and end users, each with unique goals and operational practices; (2) Second, DRL lacks prior models or established frameworks to guide the creation of meaningful long-term explanations of the agent’s behaviour in a goal-oriented RL task, and we introduce state-of-the-art approaches such as reward machine and sub-goal automata that can be universally represented and easily manipulated by logic programs and verifiably learned by inductive logic programming of answer set programs; (3) Third, most explainability approaches focus on correlation rather than causation, and we emphasise that understanding causal learning can further enhance 6G network optimisation. Together, in our judgement they form crucial enabling technologies for trustworthy services in 6G. This review offers a timely resource for academic researchers and industry practitioners by highlighting the methodological advancements needed for explainable DRL (X-DRL) in 6G. It identifies key stakeholder groups, maps their needs to X-DRL solutions, and presents case studies showcasing practical applications. By identifying and analysing these challenges in the context of 6G case studies, this work aims to inform future research, transform industry practices, and highlight unresolved gaps in this rapidly

Journal article

Corbett F, Van Zalk N, 2025,

Speech perception and hearing outcomes following pediatric bilateral cochlear implants: a scoping review of developmental contextual influences

, Frontiers in Audiology and Otology, Vol: 3, ISSN: 2813-6055

Introduction: Bilateral cochlear implantation is the typical intervention for children with severe-to-profound sensorineural hearing loss, but speech perception and hearing outcomes remain variable. This scoping review explores which contextual factors relate to speech perception and hearing outcomes following pediatric bilateral cochlear implantation based on themes aligned with Bronfenbrenner's bioecological systems theory: (1) individual; (2) microsystem; (3) mesosytem; (4) exosystem; (5) macrosystem; and (6) chronosystem.Method: PRISMA-ScR guidelines were followed to systematically search nine electronic databases with a keyword strategy. Eligible studies were published in English and included an analysis of contextual factors in relation to a behavioral speech perception or hearing outcome measure. Study quality was assessed using Quality Assessment with Diverse Studies (QuADS) criteria and the role of contextual factors in outcomes was explored with a narrative synthesis approach.Results: Twenty-three research articles met the criteria for inclusion. Contextual factors identified ranged from the proximal to distal context. Contextual factors such as non-verbal cognitive ability, social skills, cochlear implant usage, positive parent-child interactions, educational placement, auditory or oral therapy, ethnicity and prematurity were related to cochlear implant outcomes.Discussion: Relationships between contextual factors and outcomes were not consistent across developmental time or studies. Study quality and methodological limitations are discussed. Research on outcomes related to bilateral cochlear implantation should actively integrate and examine contextual factors in prospective, longitudinal designs. This approach will facilitate the development of interventions to target specific levels of the bioecological system, thereby improving outcomes for the pediatric bilateral cochlear implant recipient.

Journal article

Lim V, Khan S, Picinali L, 2025,

Towards a more accessible cultural heritage: challenges and opportunities in contextualization using 3D sound narratives

, Applied Sciences, Vol: 11, ISSN: 2076-3417

This paper reports on the exploration of potential design opportunities for social media and technology to identify issues and challenges in involving people in generating content within a cultural heritage context. The work is divided into two parts. In the first part, arguments are informed by findings from 22 in-depth semi-structured interviews with representatives of cultural institutions and with people from a general audience who recently participated in a cultural activity. The key findings show that social media could be used more extensively to achieve a deeper understanding of cultural diversity, with opportunities in redefining the expert, extending the experience space, and decentralising collaboration. To further support these findings, a case study was set up evaluating the experience of a mini audio tour with user-generated (i.e., personal stories from a local audience) vs. non user-generated (i.e., professional stories including facts) narratives. These were delivered using text and 3D sound on a mobile device. The narratives were related to a built environment in central London near world-renown museums, cultural buildings, and a royal park. Observations, a standardised spatial presence questionnaire, and a short open interview at the end of the tour were used to gain insights about participants preferences and overall experience. Thematic analysis and triangulation were used as a means for understanding and articulating opportunities for social media to better involve and engage people using user-generated narratives presented through 3D sound.

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Book chapter

Hazeri K, Childs P, 2025,

Extension of the Consensual Assessment Technique to Consumer Products: Case Studies

, Creations The Nature of Creative Products in the 21st Century, Editors: Cropley, Publisher: Palgrave MacMillan, Pages: 161-186, ISBN: 9783031824142

This edited book explores creative products (i.e. Creations) as part of the seven C's of creativity framework.

Journal article

Espinoza F, Cook D, Da Re M, Fuentes MSC, Butler CR, Calvo RAet al., 2025,

Designing AI-powered chatbots for dementia care in Peru: stakeholder engagement and field observations

, Interacting with Computers, ISSN: 0953-5438

In Peru, dementia caregivers face burnout, depression, stress and financial strain. Addressing their needs involves tackling the intricacies of resourcing, caregiving and managing emotional burdens. Chatbots could serve as a viable support mechanism for these issues in regions with limited resources. We study the perceptions of dementia caregivers in Peru regarding a chatbot tailored to offer care navigation and emotional support. We divided the study into four phases: the initial stage encompassed engaging stakeholders to understand potential design challenges; the second stage focused on the design of ‘Ana’, a chatbot for dementia caregivers; the third stage assessed the chatbot through interviews and a caregiver satisfaction survey and the fourth stage gathered contextual insights through a field study for culturally-sensitive recommendations for ‘Ana’. The findings reveal that caregivers seek immediate access to information on handling behavioural symptoms and a platform for emotional release. Moreover, ‘Ana’ was tested in two configurations—one employed predefined conversation patterns, while the other harnessed generative AI for more dynamic responses. Participants preferred the generative AI alternative of ‘Ana’ as it was perceived to be more empathic and human-like. The participants valued the generative approach despite knowing the potential risk of receiving inaccurate information. Lastly, the field observations challenge the practicality of offering care navigation due to the lack of resources available in the health system and highlight that ‘Ana’ needs to be accessible for the varying educational and technological literacy levels present in Peru. However, we found that WhatsApp could be leveraged to overcome the accessibility challenges due to its pervasiveness in Peruvian society and that Community Health Workers could play a vital role in dementia care interventions.

Journal article

Weichel M, Reder M, Daubner S, Klemens J, Burger D, Scharfer P, Schabel W, Nestler B, Schneider Det al., 2025,

Modeling the drying process in hard carbon electrodes based on the phase-field method

, PHYSICAL REVIEW MATERIALS, Vol: 9, ISSN: 2475-9953

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Citations: 2

Conference paper

Gao J, Chaudhuri B, Astolfi A, 2025,

Enhanced transient stabilization with damping assignment

, 13th IFAC Symposium on Nonlinear Control Systems, Publisher: Elsevier, ISSN: 2405-8963

The paper proposes an analytical nonlinear control approach for enhancing the transient performance of lossy multi-machine power systems. The prominent feature of thisapproach lies in the inclusion of damping assignment, whereby the oscillation of the power system frequency is dampened out more effectively. In this regard, the proposed control approach is said to achieve enhanced transient stabilization, which is desirable in practical applications.A case study demonstrates the enhanced performance of the proposed control approach over existing nonlinear control approaches.

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Journal article

Ballou N, Vuorre M, Hakman T, Magnusson K, Przybylski AKet al., 2025,

Perceived value of video games, but not hours played, predicts mental well-being in casual adult Nintendo players

, Royal Society Open Science, Vol: 12, ISSN: 2054-5703

Studies on video games and well-being often rely on self-report measures or data from a single game. Here, we study how 703 casually engaged US adults’ time spent playing for over 140 000 h across 150 Nintendo Switch games relates to their life satisfaction, affect, depressive symptoms and general mental well-being. We replicate previous findings that playtime over the past two weeks does not predict well-being, and extend these findings to a wider range of timescales (1 h to 1 year). Equivalence tests were inconclusive, and thus we do not find evidence of absence, but results suggest that practically meaningful effects lasting more than 2 h after gameplay are unlikely. Our non-causal findings suggest substantial confounding would be needed to shift a meaningful true effect to the observed null. Although playtime was not related to well-being, players’ assessments of the value of game time—so-called gaming life fit—were. Results emphasize the importance of defining the gaming population of interest, collecting data from more than one game, and focusing on how players integrate gaming into their lives rather than the amount of time spent.

Journal article

Bayram B, Meijer D, Barumerli R, Spierings M, Baumgartner R, Pomper Uet al., 2025,

Bayesian prior uncertainty and surprisal elicit distinct neural patterns during sound localization in dynamic environments.

, Sci Rep, Vol: 15

Estimating the location of a stimulus is a key function in sensory processing, and widely considered to result from the integration of prior information and sensory input according to Bayesian principles. A deviation of sensory input from the prior elicits surprisal, depending on the uncertainty of the prior. While this mechanism is increasingly understood in the visual domain, much less is known about its implementation in audition, especially regarding spatial localization. Here, we combined human EEG with computational modeling to study auditory spatial inference in a noisy, volatile environment and analyzed behavioral and neural patterns associated with prior uncertainty and surprisal. First, our results demonstrate that participants indeed used prior information during periods of stable environmental statistics, but showed evidence of surprisal and discarded prior information following environmental changes. Second, we observed distinct EEG activity patterns associated with prior uncertainty and surprisal in both the time- and time-frequency domain, which are in line with previous studies using visual tasks. Third, these EEG activity patterns were predictive of our participants' sound localization error, response uncertainty, and prior bias on a trial-by-trial basis. In summary, our work provides novel behavioral and neural evidence for Bayesian inference during dynamic auditory localization.

Journal article

Zou Y, Zhao C, Childs P, Luh D, Tang Xet al., 2025,

User experience design for online sports shoe retail platforms: an empirical analysis based on consumer needs

, Behavioral Sciences, Vol: 15, ISSN: 2076-328X

Digital technologies represented by AR (Augmented Reality), VR (Virtual Reality), and digital twins, along with the expansion of metaverse platforms and digital marketing concepts, have attracted the attention of numerous sports fashion product consumers and brands, particularly in the category of sports shoes. Therefore, in the context of digital technologies, understanding the factors that affect consumer experience and the preferences in the online purchasing process of sports shoes is very important. This study employs Latent Dirichlet Allocation topic analysis to analyze 44,110 online user posts and comments from social platforms, extracting thematic elements of consumer experience needs for purchasing sports shoes online. The information obtained is further encoded and designed into a questionnaire, which is then utilized alongside the Kano model to analyze the overall preferences of consumer experience needs. The results indicate that webpage design and basic product information are considered as Must-be attributes for user experience needs; providing information on after-sales service policies and product comment, products’ special feature information, and online size testing are recognized as Performance attributes. Additionally, high-tech interaction methods, visual presentation, personalized customization, virtual try-on, apparel matching recommendations, and dressing scenario recommendations are identified as Attractive attributes. The study reveals that in the context of new digital technology development, the online shopping experience for sports shoes is enhanced across four dimensions: platform experience augmentation, product experience augmentation, user demand augmentation, and interactive experience augmentation. These four dimensions collectively constitute the holistic experience design for the online retail platform. Therefore, this research provides case references and theoretical insights for researchers and developers in the fields of

Journal article

Wang B, Han J, Zhao X, Yin Y, Chen L, Childs Pet al., 2025,

Creative combinational design through generative AI in different dimensional representations: an exploration

, Design and Artificial Intelligence, Vol: 1, ISSN: 3050-7413

Although generative AI models are increasingly integrated into creative work, there is limited evidence on how dimensional representations of generative AI—text, image, and 3D—impact the creative process. Identifying these effects aids researchers in selecting suitable models for developing generative design. Through two empirical studies, this research examines the capacity of generative models with varying dimensions to support combinational ideation and influence the creative design process. The results indicate that generative models in different dimensions demonstrate varying levels of creative combinational ideation. Generative AI supports combinational ideation by providing more ideas in divergent stages rather than helping decision-making in convergent stages. These results help inform AI design developers in choosing models and integrating models for combination.

Journal article

Mansfield KL, Ghai S, Hakman T, Ballou N, Vuorre M, Przybylski AKet al., 2025,

From social media to artificial intelligence: improving research on digital harms in youth.

, Lancet Child Adolesc Health, Vol: 9, Pages: 194-204

In this Personal View, we critically evaluate the limitations and underlying challenges of existing research into the negative mental health consequences of internet-mediated technologies on young people. We argue that identifying and proactively addressing consistent shortcomings is the most effective method for building an accurate evidence base for the forthcoming influx of research on the effects of artificial intelligence (AI) on children and adolescents. Basic research, advice for caregivers, and evidence for policy makers should tackle the challenges that led to the misunderstanding of social media harms. The Personal View has four sections: first, we conducted a critical appraisal of recent reviews regarding effects of technology on children and adolescents' mental health, aimed at identifying limitations in the evidence base; second, we discuss what we think are the most pressing methodological challenges underlying those limitations; third, we propose effective ways to address these limitations, building on robust methodology, with reference to emerging applications in the study of AI and children and adolescents' wellbeing; and lastly, we articulate steps for conceptualising and rigorously studying the ever-shifting sociotechnological landscape of digital childhood and adolescence. We outline how the most effective approach to understanding how young people shape, and are shaped by, emerging technologies, is by identifying and directly addressing specific challenges. We present an approach grounded in interpreting findings through a coherent and collaborative evidence-based framework in a measured, incremental, and informative way.

Journal article

Simard JD, Moreschini A, Astolfi A, 2025,

Parameterization of All Differential-Algebraic Moment Matching Interpolants

, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 70, Pages: 1875-1882, ISSN: 0018-9286

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Citations: 1

Journal article

Wang Q, Dai H-N, Yang J, Guo C, Childs P, Kleinsmann M, Guo Y, Wang Pet al., 2025,

Learning-based artificial intelligence artwork: methodology taxonomy and quality evaluation

, ACM Computing Surveys, Vol: 57, ISSN: 0360-0300

With the development of the theory and technology of computer science, machine or computer painting is increasingly being explored in the creation of art. Machine-made works are referred to as artificial intelligence (AI) artworks. Early methods of AI artwork generation have been classified as non-photorealistic rendering, and, latterly, neural style transfer methods have also been investigated. As technology advances, the variety of machine-generated artworks and the methods used to create them have proliferated. However, there is no unified and comprehensive system to classify and evaluate these works. To date, no work has generalized methods of creating AI artwork including learning-based methods for painting or drawing. Moreover, the taxonomy, evaluation, and development of AI artwork methods face many challenges. This article is motivated by these considerations. We first investigate current learning-based methods for making AI artworks and classify the methods according to art styles. Furthermore, we propose a consistent evaluation system for AI artworks and conduct a user study to evaluate the proposed system on different AI artworks. This evaluation system uses six criteria: beauty, color, texture, content detail, line, and style. The user study demonstrates that the six-dimensional evaluation index is effective for different types of AI artworks.

Conference paper

Chen K, Zhang K, Landau ID, Astolfi Aet al., 2025,

Continuous-time adaptive control with dynamic adaptation gain

, 2024 IEEE 63rd Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 2815-2820

This paper investigates a class of continuous-time parameter identifiers with the so-called “dynamic adaptation gain (DAG)”, inspired by its discrete-time counterpart [1]. A modular control law is first presented: this helps re-parametrize the system and highlight the required properties for the identifier. Then, a dynamic adaptation gain is constructed using a strictly passive system, strengthened by a feedthrough path: the resulting DAG is input strictly passive. Analysis shows that the identifier with the proposed DAG satisfies specific signal properties. An integrated analysis of both the control law and the identifier establishes boundedness of all closedloop signals and state convergence. The convergence of the parameter estimate is also established under a persistence of excitation condition. Finally, an example inspired by a pathfollowing problem demonstrates the convergence improvement achieved by the proposed DAG.

Journal article

Griggs WM, Ghosh R, Marecek J, Shorten RNet al., 2025,

Unique ergodicity in feedback interconnections of ensembles of agents

, INTERNATIONAL JOURNAL OF CONTROL, ISSN: 0020-7179

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Enhanced transient stabilization with damping assignment

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