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  • Journal article
    Martin V, Engel I, Picinali L, 2025,

    Effects of geometrical acoustics model simplification on binaural reverberation

    , IEEE Transactions on Audio, Speech and Language Processing, Vol: 33, Pages: 3480-3493, ISSN: 1558-7916

    Virtual reverberation rendering typically requires detailed information about room geometry and surface acoustic characteristics. While comprehensive modeling approaches can account for all aspects of an acoustic environment, they often incur high computational cost that may be perceptually unnecessary. Therefore, finding a trade-off between perceptual authenticity and model complexity becomes a relevant challenge. This study investigates such compromise through the use of geometrical acoustics to render Ambisonics-based binaural reverberation. The accuracy of the rendering is determined, among other factors, by its fidelity to the room’s geometry and to the acoustic properties of its materials. In particular, the model fidelity is varied by simplifying the room geometry and frequency resolution of the absorption coefficients. Several decimated models based on a single room were perceptually evaluated using a multi-stimulus comparison method. Additionally, these differences were numerically assessed through the comparison of acoustic parameters of the rendered reverberation. According to numerical and perceptual evaluations, lowering the frequency resolution of absorption coefficients can have a significant impact on the perception of reverberation, while a smaller impact was observed when decimating the geometry of the model.
  • Journal article
    Vamvakeros A, Vamvakeros A, Papoutsellis E, Dong H, Docherty R, Beale AM, Cooper SJ, Jacques SDMet al., 2025,

    nDTomo: a modular python toolkit for X-ray chemical imaging and tomography

    , Digital Discovery, ISSN: 2635-098X

    nDTomo is a Python-based software suite for the simulation, reconstruction and analysis of X-ray chemical imaging and computed tomography data. It provides a collection of Python function-based tools designed for accessibility and education as well as a graphical user interface. Prioritising transparency and ease of learning, nDTomo adopts a function-centric design that facilitates straightforward understanding and extension of core workflows, from phantom generation and pencil-beam tomography simulation to sinogram correction, tomographic reconstruction and peak fitting. While many scientific toolkits embrace object-oriented design for modularity and scalability, nDTomo instead emphasises pedagogical clarity, making it especially suitable for students and researchers entering the chemical imaging and tomography field. The suite also includes modern deep learning tools, such as a self-supervised neural network for peak analysis (PeakFitCNN) and a GPU-based direct least squares reconstruction (DLSR) approach for simultaneous tomographic reconstruction and parameter estimation. Rather than aiming to replace established tomography frameworks, nDTomo serves as an open, function-oriented environment for training, prototyping, and research in chemical imaging and tomography.
  • Journal article
    Hogg A, Barumerli R, Daugintis R, Poole K, Brinkmann F, Picinali L, Geronazzo Met al., 2025,

    Listener acoustic personalisation challenge - LAP24: head-related transfer function upsampling

    , IEEE Open Journal of Signal Processing, Vol: 6, Pages: 926-941, ISSN: 2644-1322

    Head-related transfer functions (HRTFs) often play a crucial role in spatial hearing, immersive audio applications for virtual reality (VR) and augmented reality (AR), and help in improving hearing assistive devices. The Listener Acoustic Personalisation (LAP) challenge 2024 aimed at advancing research in spatial audio personalisation, with a focus on head-related transfer functions (HRTFs). The challenge was split into two tasks: Task 1 was on HRTF harmonisation, and Task 2 dealt with spatial HRTF upsampling. This paper presents the results and reports the findings related to Task 2 of the LAP challenge. The submissions to Task 2 employed both algorithmic and machine learning-based approaches, which were evaluated on three key spatial audio objective metrics, including the log-spectral distortion (LSD), interaural time difference (ITD), and the interaural level difference (ILD). The results highlighted the strengths and limitations of various upsampling techniques, with learning-based methods demonstrating superior performance at lower sparsity levels. In terms of the LSD, seven of the submissions achieved an impressive performance of less than 5 dB when upsampling from only three measurement points. The results also highlighted that most submissions were often not able to outperform a generic HRTF created by averaging the HRTFs in the training dataset. One of the main contributions of this paper is that it showcases the limitations of objective metrics when it comes to evaluating HRTF upsampling. Therefore, this paper argues that a more holistic approach is needed going forward, which should include the integration of multiple perceptually relevant measures, as this is the only way to ensure a well-rounded assessment of HRTF upsampling quality.
  • Journal article
    Perera S, Bornassi S, Ghajari M, Nanayakkara Tet al., 2025,

    Joints with angle dependent damping can help to reduce impact forces in robots

    , Scientific Reports, Vol: 15, ISSN: 2045-2322

    This paper investigates how a new angle-dependent damper design can help a robot to reduce collision forces. We designed a fluid-viscous angle-dependent damper by smoothly changing the clearance between the stationary and moving parts. Analytical and numerical simulation-based predictions were experimentally tested. Analytical modelling shows that angle-dependent damping has a 48%reduction in peak forces when compared to constant damping. Numerical simulations show that variable-gap dampers can change damping by 134× during a 10× gap change. The experimental findings confirm the analytical predictions by reducing collision force by up to 10%. These findings suggest that the angle-dependent variable damping solution could be used for robots that experience collisions such as industrial robotic manipulators, legged robots, perching robots, or robots that catch moving objects.
  • Conference paper
    Dong W, Bhattacharya D, Kobayashi A, Seino A, Tokuda F, Huang X, Tang K, Tien NC, Kosuge Ket al., 2025,

    Precise Top-Layer Fabric Segmentation for Fabric Destacking with Edge- and Shape-Aware Deep Networks

    , 2025 IEEE International Conference on Mechatronics and Automation (ICMA), Publisher: IEEE, Pages: 1343-1348
  • Journal article
    Watanabe T, Li J, Nakagami G, Dai M, Miura Y, Torii M, Nanayakkara T, Hirai Set al., 2025,

    Special issue on nursing robotics (Part I)

    , ADVANCED ROBOTICS, Vol: 39, Pages: 935-935, ISSN: 0169-1864
  • Journal article
    Zhou H, Li H, Zhao Y, Childs PRN, Li Net al., 2025,

    Image-based Artificial Intelligence-driven modelling for blank shape optimisation in sheet metal forming

    , Materials and Design, Vol: 256, ISSN: 0264-1275

    Design for manufacturing is essential to fully exploit the potential of emerging materials and processing technologies. However, traditional trial-and-error optimisation often exhibits inferior performance in manufacturability-driven problems, particularly when handling complex shapes. Surrogate modelling and optimisation have been widely investigated for efficiently predicting simulation results and enhancing manufacturability. Nevertheless, existing methods are mostly constrained by fixed shape parameterisation schemes, limiting their flexibility and effectiveness. To overcome this limitation, this research develops a non-parametric optimisation framework, validated on a sheet metal forming case study, specifically the blank shape optimisation of a hot-stamped B-pillar. The framework integrates an auto-decoder, serving as a differentiable blank shape generator, a convolutional neural network (CNN)-powered surrogate model for manufacturability evaluation, and an Adam optimiser for automated shape optimisation. The surrogate model predicts thickness distributions from the signed distance fields (SDFs) of blank shapes, which are generated by the auto-decoder from latent vectors; based on the predictions, the optimiser iteratively updates the latent vectors to acquire a blank shape with optimised manufacturability. The proposed framework demonstrates superior performance in terms of the accuracy of thickness distribution prediction, the fidelity of blank shape generation, and the efficiency of blank shape optimisation.
  • Journal article
    Yin Y, Wang B, Zuo H, Liu R, Vohra SI, Haydon-Rowe S, Childs PRNet al., 2025,

    Abilities of design professors to distinguish design assignments generated by students and AI

    , Proceedings of the Design Society, Vol: 5, Pages: 319-328, ISSN: 2732-527X

    This study aims to detect the ability of professors to distinguish design assignments generated by students with and without using AI. Ten students were recruited to undertake a conceptual design task twice, one with and one without the help of AI. 105 higher-education associate, assistant and full professors from industrial and product design programmes were recruited to assess the generated designs using a 7-point Likert Scale with nine indexes. The results indicate that assessors have moderate ability to distinguish between design assignments of students using AI and those where students did not use AI. Three cues to suggest the risk of the design assignment is made with AI instead of students who did not use AI were identified. By considering the three cues, lecturers distinguish design assignments generated by students with or without AI.
  • Journal article
    Sadek M, Calvo RA, Mougenot C, 2025,

    The value-sensitive conversational agent co-design framework

    , International Journal of Human-Computer Interaction, Vol: 41, Pages: 9533-9564, ISSN: 1044-7318

    Conversational agents (CAs) are rapidly advancing across industry and academia and it is crucial to consider the values embedded within these systems. Value-sensitive design practices have benefited AI-based systems, but have not yet been widely applied to CAs. This paper introduces the Value-Sensitive Conversational Agent (VSCA) Framework. The framework uses collaborative design (co-design) activities to guide CA creators and CA users to collaboratively create three key artefacts that elicit CA users’ values and are technically useful for CA creators to drive implementation forward, resulting in value embodied CA prototypes. The paper presents the practical framework and toolkit, followed by a mixed-method evaluation through design workshops, semi-structured interviews, and a comparative survey. Results show that the framework and toolkit increase CA creators’ value-sensitivity, empower CA users, enhance collaboration, and produce value-embodied prototypes. Based on this work, we offer 14 guidelines to practically support value sensitivity in CAs.
  • Journal article
    Prawda K, Meyer-Kahlen N, Schlecht SJ, 2025,

    Cropping room impulse responses using unimodal regression of their covariance.

    , JASA Express Lett, Vol: 5

    The presence of unavoidable background noise limits the signal-to-noise ratio in measured room impulse responses (RIRs). A common solution is to crop the RIR to the time interval where the signal dominates the background noise, but finding the correct onset and truncation points is challenging. It usually requires estimating the sound decay rate and noise floor, which is burdened with uncertainty. In this study, we propose an RIR cropping method based on the covariance between two repeated RIRs and its inherent monotonicity. Evaluation on measured RIRs shows the proposed method is highly robust in different scenarios and outperforms state-of-the-art algorithms.
  • Journal article
    Marggraf-Turley N, Shiell MM, Pontoppidan NH, Cappotto D, Picinali Let al., 2025,

    Electroencephalographic decoding of sound location: comparing free-field to headphone-based non-individual head-related transfer functions

    , Journal of the Acoustical Society of America, Vol: 158, Pages: 859-870, ISSN: 0001-4966

    Sound source localization relies on spatial cues, such as interaural time differences, interaural level differences, and monaural spectral cues. Individually measured head-related transfer functions (HRTFs) facilitate precise spatial hearing but are impractical to measure, necessitating non-individual HRTFs, which may compromise localization accuracy and externalization. To further investigate this phenomenon, the neurophysiological differences between free-field and non-individual HRTF listening are explored by decoding sound locations from EEG-derived event-related potentials. Twenty-two participants localized stimuli under both conditions with EEG responses recorded and logistic regression classifiers trained to distinguish sound source locations. Lower cortical response amplitudes were observed for KEMAR compared to free-field, especially in front-central and occipital-parietal regions. ANOVA identified significant main effects of auralization condition and location on decoding accuracy (DA), which was higher in free-field and interaural-cue-dominated locations. DA negatively correlated with front-back confusion rates, linking neural DA to perceptual confusion. These findings demonstrate that headphone-based non-individual HRTFs elicit lower amplitude cortical responses to static, azimuthally varying locations than free-field conditions. The correlation between EEG-based DA and front-back confusion underscores neurophysiological markers' potential for assessing spatial auditory discrimination.
  • Journal article
    Ramanathan V, Head P, Eltahir E, Daigger GT, Smith CE, Yokohari M, Childs P, Ma J, Yu Ket al., 2025,

    Climate Design: Holistic Solution for Climate Resilience

    , LANDSCAPE ARCHITECTURE FRONTIERS, Vol: 13, Pages: 87-97, ISSN: 2096-336X
  • Journal article
    Ren X, Zhao Y, 2025,

    Hydrogen therapy for ischemic injuries

    , NATURE CHEMICAL ENGINEERING, Vol: 2, Pages: 467-469
  • Conference paper
    Lintunen EM, Ady NM, Deterding S, Guckelsberger Cet al., 2025,

    Towards a formal theory of the need for competence via computational intrinsic motivation

    , CogSci 2025, Pages: 2175-2183

    Computational modelling offers a powerful tool for formalising psychological theories, making them more transparent, testable, and applicable in digital contexts. Yet, the question often remains: how should one computationally model a theory? We provide a demonstration of how formalisms taken from artificial intelligence can offer a fertile starting point. Specifically, we focus on the "need for competence", postulated as a key basic psychological need within Self-Determination Theory (SDT)—arguably the most influential framework for intrinsic motivation (IM) in psychology. Recent research has identified multiple distinct facets of competence in key SDT texts: effectance, skill use, task performance, and capacity growth. We draw on the computational IM literature in reinforcement learning to suggest that different existing formalisms may be appropriate for modelling these different facets. Using these formalisms, we reveal underlying preconditions that SDT fails to make explicit, demonstrating how computational models can improve our understanding of IM. More generally, our work can support a cycle of theory development by inspiring new computational models, which can then be tested empirically to refine the theory. Thus, we provide a foundation for advancing competence-related theory in SDT and motivational psychology more broadly.
  • Journal article
    Shen K, Yao X, Song H, Shi W, Zheng C, Hong X, Yan Y, Liu X, Zhu L, An Y, Song T, Shafqat MB, Ma C, Zheng L, Gao P, Liu Y, Safari M, Zhao Y, Pang Qet al., 2025,

    All-solid-state batteries stabilized with electro-mechano-mediated phosphorus anodes

    , ENERGY & ENVIRONMENTAL SCIENCE, Vol: 18, Pages: 7568-7578, ISSN: 1754-5692
  • Journal article
    Daugintis R, Barumerli R, Geronazzo M, Pauwels J, Picinali L, Poole KCet al., 2025,

    Listener acoustic personalisation challenge – LAP24: head-related transfer function dataset harmonization

    , IEEE Open Journal of Signal Processing, Vol: 6, Pages: 950-964, ISSN: 2644-1322

    Big data analysis and collation for data-driven head-related transfer function (HRTF) personalization methods are often hindered by systematic differences between HRTF datasets. To address this issue, we designed Task 1 of the inaugural listener acoustic personalisation (LAP) challenge. Researchers were invited to propose strategies for harmonizing HRTFs from a collection of eight different datasets so that dataset-specific artifacts were mitigated while preserving the perceptually relevant attributes of the original HRTFs. Defining the two-sided task required a deeper assessment of the acoustic and perceptual HRTF descriptions to find an evaluation framework that encompassed the two domains. Consequently, a two-stage evaluation was devised to assess the submissions. First, an auditory sound localization model was used to test the perceptual validity of the harmonized HRTFs by estimating the difference in sound localization performance between the original and the harmonized versions. Then, a machine learning classifier was employed to differentiate harmonized HRTF datasets, and its accuracy was used to rank submissions. Three submissions were received, and one was declared a winner according to the evaluation criteria. Further analysis of the submissions revealed some limitations of the evaluation system, prompting a comprehensive review of the task’s inherent complexities. This paper serves as a systematic account of the challenge and relevant considerations, intended to guide future advancements in the field of HRTF personalization research.
  • Journal article
    Tan R, Baker C, Xiancheng Y, Ghajari Met al., 2025,

    Superior linear and comparable rotational protection of an air-filled helmet versus foam helmets

    , Scientific Reports, Vol: 15, ISSN: 2045-2322

    Air-filled chambers offer a promising approach for designing lightweight and portable bicycle helmets, yet their effectiveness in real-world cycling accidents, particularly under oblique impacts, remains unexplored. Here, for the first time, we evaluated the brain injury mitigation performance of a commercially available air-filled helmet, Ventete aH-1, under oblique impacts, and compared it with three conventional cycle helmets, ranking high, middle and low in a recent study of 30 cycle helmets. Helmets were fitted to a new headform with more biofidelic physical properties than other existing headforms, allowing for more accurate measurements of linear and rotational motion during impacts. The helmeted headform was subjected to impacts to the front, front-side, side and rear against a 45° anvil at 6.5 m/s. The risk of linear and rotational injuries was calculated using risk functions based on PLA (peak linear acceleration) and BrIC (brain injury criterion) and exposure weighting. The PLA and linear risk were lower for the air-filled helmet than the EPS helmets in all impact locations. The air-filled helmet showed a 44% reduction in overall linear brain injury risk compared to the best-performing EPS helmet, attributed to its nearly twice as long impact duration. The air-filled helmet’s rotational performance compared to the EPS helmets was dependent on the impact location, with its overall rotational risk being slightly better than the EPS helmet ranked middle. Our study shows that air-filled chambers have the potential to provide superior protection compared with EPS liner helmets under oblique impacts. We hope our results will inspire new helmet designs which adopt air-filled chambers to improve brain injury protection and address portability concerns that limit helmet adoption.
  • Journal article
    Dahari A, Docherty R, Kench S, Cooper SJet al., 2025,

    Prediction of Microstructural Representativity From A Single Image

    , ADVANCED SCIENCE
  • Journal article
    Liu D, Baldi S, Yang K, Astolfi Aet al., 2025,

    Equipping Vehicular Platoons With Partial-State Immersion and Invariance Adaptation

    , IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, ISSN: 1063-6536
  • Journal article
    Wang Z, Gupta S, Page F, Agg C, Spivey AC, Hazeri K, Zou Y, Zhao C, Lucas C, Childs Pet al., 2025,

    Group project practices and guidance in higher education contexts

    , Frontiers in Education, Vol: 10, ISSN: 2504-284X

    Anecdotal good practice in group projects is widely available. In the academic context group project work offers potential for real world experience development along with enabling activities to be undertaken within limited resources. Nevertheless, concerns exist regarding aspects such as fairness, burden and unpopularity. This paper provides a review of commonly cited best practice for group projects, supplemented by a cross-university review undertaken by students of group projects at Imperial in combination with guidance from three other universities. Arising highlighted good practice principles include prioritization, holding a kick-off meeting, establishment of project scope and objectives, attention to group composition, resource planning, change management, project planning, risk management, documentation, communication, cooperation, culture and psychological safety, dependability, sense of purpose, conflict management and feedback. From the extensive body of guidance available it is evident that we could learn more from industrial approaches to project management. However, it is also acknowledged that maximizing outcomes may not maximize learning, especially for academically weaker and stronger students. A recommendation arising from practice in some modules and industry includes ongoing attention to project management training and role development during a project so that practitioners can continue to learn and upskill within a project and specific role, rather than relying on training sessions before a project.
  • Journal article
    Carman F, Bresme F, Wu B, Dini D, Ewen JPet al., 2025,

    Water nanofilms mediate adhesion and heat transfer at hematite-hydrocarbon interfaces

    , Advanced Materials Interfaces, Vol: 12, ISSN: 2196-7350

    A detailed understanding of nanoscale heat transport at metal oxide-hydrocarbon interfaces is critical for many applications that require efficient thermal management. Under ambient conditions, water nanofilms are expected to form at these interfaces, but these are rarely accounted for in simulations. Using molecular dynamics simulations, it is shown that water nanofilms at the hydroxylated hematite/poly-α-olefin (PAO) interface significantly affect wettability and thermal transport. Including water nanofilms improves agreement with experimental work of adhesion, which cannot be replicated with anhydrous systems using realistic solid–liquid interactions. For water films thicker than one monolayer, interfacial thermal resistance (ITR) converges to a consistent value, independent of solid–liquid interaction strength. This value is dominated by the ITR at the water/PAO interface. The ITR at the water/PAO interface is dependent on the surface area between the water film and the PAO and the magnitude of the interfacial potential. These simulations provide a more precise estimate of ITR at the hematite/PAO interface by accounting for surface hydration expected in experiments under ambient conditions. This study offers crucial insights into the roles of surface hydroxylation and water nanofilms in controlling wettability and thermal transport at industrially important interfaces.
  • Journal article
    Fornier Z, Leclere V, Pinson P, 2025,

    Fairness by design in shared-energy allocation problems

    , COMPUTATIONAL MANAGEMENT SCIENCE, Vol: 22, ISSN: 1619-697X
  • Conference paper
    Binyamini Ben-Meir N, Healy PGT, Deterding S, 2025,

    Domestic cultures of plant care: a moss terrarium probe

    , New York, New York, Designing Interactive Systems Conference (DIS ’25), Publisher: ACM

    Houseplants are increasingly being used as part of interactive sys- tems that aim to foster pro-environmental concern and awareness of more-than-human life. Yet such interventions rely on conflicting and untested assumptions about how people relate to houseplants. We therefore studied domestic plant care in 11 purposefully sampled households, applying a sensor-equipped moss terrarium as a living ‘thing ethnography’ probe, supplemented with semi-structured in- terviews. We find that social and intergenerational cultures of plant care inform people’s individual concern and accountability through constituents and mechanisms like gift-giving, signalling, knowledge transfer, or joint practical care. We identify five domestic cultures of plant care in our sample, each of which frames plants differently and leads to different practical approaches to plant care. We propose design considerations that emphasise enculturation and shared care over individual behaviour change and reframe houseplants from decorative objects into living household members.
  • Journal article
    Daubner S, Weichel M, Reder M, Schneider D, Huang Q, Cohen AE, Bazant MZ, Nestler Bet al., 2025,

    Simulation of intercalation and phase transitions in nano-porous, polycrystalline agglomerates

    , NPJ COMPUTATIONAL MATERIALS, Vol: 11
  • Journal article
    Zhou H, Zhao Y, Li H, Pfaff T, Li Net al., 2025,

    A multi-level graph-based surrogate model for real-time high-fidelity sheet forming simulations

    , Advanced Engineering Informatics: the science of supporting knowledge-intensive activities, Vol: 66, ISSN: 0954-1810

    Surrogate models with structured data representations, mainly images and graphs, have been widely investigated in various domains, including automotive manufacturing. Despite advances, existing approaches still face significant challenges in terms of accuracy, efficiency, and generalisability. To address these challenges, a promising direction is to combine the advantages of both images and graphs. This study proposes a graph-based surrogate model, which has a multi-level architecture with enhanced graph convolutional operations using image-inspired spatial edge weights. To evaluate its performance, three additional graph-based surrogate models are developed for comparison, each differing in the formulation of spatial edge weights. All four models are assessed on a real-world hot-stamping B-pillar case study, which involves variations in blank shapes under multiple parameterisations and post-stamped thickness distributions exhibiting complicated local patterns. The proposed architecture significantly outperforms the three comparison models, achieving high accuracy with a relatively low computational burden during training and deployment. Furthermore, it demonstrates strong robustness in hyperparameter calibration and shows the potential for generalisation to other manufacturability-related real-time simulation problems. This study presents an effective methodology for future surrogate model development by integrating the advantages of different structured data representations.
  • Conference paper
    Bhattacharjee D, Mao J, Moreschini A, Scarciotti G, Astolfi Aet al., 2025,

    Using Explicit Generators and Filters in Two-Sided Moment Matching

    , Pages: 532-537, ISSN: 2405-8971

    We study the two-sided moment matching problem for time-varying systems connected to an explicit signal generator and an explicit filter. We first provide the notion of moment in a time-varying setting for both the standard and the swapped interconnection. By leveraging these notions of moment, we derive reduced-order models that achieve two-sided moment matching. Finally, we illustrate the result on a benchmark example.
  • Journal article
    Chen L, Cai Z, Jiang Z, Sun L, Childs P, Zuo Het al., 2025,

    A knowledge graph-based bio-inspired design approach for knowledge retrieval and reasoning

    , Journal of Engineering Design, Vol: 36, Pages: 1321-1351, ISSN: 0954-4828

    Bio-inspired Design (BID) is a method that draws principles from biological systems to solve complex real-world problems. While diverse knowledge-based tools have served BID, the retrieval and reasoning capabilities of knowledge graphs have not been explored in BID. This study introduces a novel knowledge graph-based BID approach, exploiting the power of knowledge graphs to support BID. In the approach, a comprehensive ontology is defined and then applied to construct a BID-specific knowledge graph, enabling efficient representation of the diverse and rich biological knowledge. The knowledge graph supports BID by facilitating knowledge retrieval and reasoning. Retrieval in BID is accomplished by finding potential links between biological systems and relevant design applications. Reasoning in BID is supported by a link prediction model that follows the design process of mapping from biological systems to design applications. Two case studies are conducted to demonstrate the effectiveness of the approach. The first case shows that our approach outperforms other benchmarks in retrieving related biological knowledge, and the second case presents how the link prediction model aids in generating relevant and inspirational design ideas.
  • Journal article
    Zhao Y, Du H, Kang Y, Zhang J, Lan B, Guo Z, Titirici M-M, Zhao Y, Tavajohi N, Kang F, Li Bet al., 2025,

    Spent battery regeneration for better recycling

    , NATURE REVIEWS MATERIALS, ISSN: 2058-8437
  • Journal article
    Tarantino L, Astolfi A, Sassano M, 2025,

    To play or not to play: A characterization of the marginal contribution of the opponent in a class of LQ differential games☆

    , AUTOMATICA, Vol: 177, ISSN: 0005-1098
  • Journal article
    Baker CE, Ghajari M, 2025,

    How do demographic factors, non-standard and out-of-position seating affect vehicle occupant injury outcomes in road traffic collisions?

    , SAFETY SCIENCE, Vol: 187, ISSN: 0925-7535

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