University of Cambridge — CS Research

Computer science research from Cambridge, covering machine learning, programming languages, security, and distributed systems.

Sample of the collection (25 of 2,074 items)

• AI-assisted Living Evidence Databases for Conservation Science University of Cambridge Living evidence databases offer a robust and dynamic alternative to static systematic reviews but require a resilient technical…
• Artificial intelligence transformations in geotechnics: progress, challenges and future enablers University of Cambridge Our reliance on the underground space to deliver critical civil engineering infrastructure is growing: to accommodate utility and…
• Achieving 100% amplitude modulation depth in the terahertz range with graphene-based tuneable capacitance metamaterials University of Cambridge Effective control of terahertz radiation requires fast and efficient modulators with a large modulation depth-a challenge that is often…
• Decoupling the catalytic and degradation mechanisms of cobalt active sites during acidic water oxidation Monash University Abstract Advancement of iridium-free catalysts for the low-pH oxygen evolution reaction (OER) is required to enable multi-gigawatt-scale…
• Halogen‐Bonded Liquid Crystal Elastomers as Initiator‐Free Photochemical Actuators Tampere University Photochemically driven liquid crystal elastomer (LCE) actuators require precise arrangement and sufficiently high concentration of…
• A framework for evaluating the chemical knowledge and reasoning abilities of large language models against the expertise of chemists Helmholtz Institute Jena Large language models (LLMs) have gained widespread interest owing to their ability to process human language and perform tasks on which…
• Users’ experiences of park accessibility and attractiveness based on online review analytics Al-Azhar University Understanding public experiences of urban parks is crucial for their sustainable and effective management. While traditional surveys…
• Automatic Prediction of Molecular Properties Using Substructure Vector Embeddings within a Feature Selection Workflow Rutherford Appleton Laboratory Machine learning (ML) methods provide a pathway to accurately predict molecular properties, leveraging patterns derived from…
• Challenges and opportunities of supply chain traceability: insights from emergent agri-food sector Agricultural University of Athens Purpose Traceability systems (TS) have enabled significant improvements in supply chain management. Despite these advancements, there is…
• Sustainable, Wearable, and Eco‐Friendly Electronic Textiles University of the West of England Wearable electronic textiles (e‐textiles) with embedded electronics offer promising solutions for unobtrusive, real‐time health…
• Novel 4F² Multi-Bit Dual-Gate 2T0C for High-Density DRAM with Improved Vertical-Channel IGZO TFTs by Self-Aligned Single-Step Process Institute of Microelectronics For the first time, we propose and experimentally demonstrate one novel 4<sup xmlns:mml="http://www.w3.org/1998/Math/MathML"…
• Chip-scale sensor for spectroscopic metrology University of Cambridge Miniaturized spectrometers hold great promise for in situ, in vitro, and even in vivo sensing applications. However, their size…
• Improving electrocatalytic OER activity of perovskites through insertion of ternary B-site metals University of Exeter Anion exchange membrane water electrolysers (AEMWEs) demonstrate promise for efficient and cost-effective hydrogen production. However,…
• Snail shell derived magnetic nanocatalysts for biodiesel production: Process optimization through response surface methodology, kinetics, and thermodynamic studies National Institute Of Technology Silchar In this study, calcium oxide-magnetite (CaO-Fe₃O₄) nanocomposites (NCs) were synthesized from waste inorganic biomass (snail shells)…
• Stakeholder Involvement for Responsible AI Development: A Process Framework University of Cambridge Stakeholder involvement (ShI) is increasingly promoted for responsible AI development; however, we lack insights into the actual process…
• Digital twins for urban underground space University of Cambridge Digital twins (DTs) offer promising benefits to address several inherent problems in underground construction, yet confusion surrounds…
• Enhancing Cybersecurity through AI-Powered Security Mechanisms University of Cambridge In the rapidly evolving landscape of digital technology, the proliferation of interconnected systems has brought unprecedented…
• Towards autonomous supply chains: Definition, characteristics, conceptual framework, and autonomy levels University of Cambridge Recent global disruptions, such as the COVID-19 pandemic and the ongoing geopolitical conflicts, have profoundly exposed vulnerabilities…
• Towards trustworthy AI for link prediction in supply chain knowledge graph: a neurosymbolic reasoning approach University of Cambridge Modern supply chains are complex and interlinked, resulting in increased network risk exposure for companies. Digital Supply Chain…
• When and why does motor preparation arise in recurrent neural network models of motor control? University of Cambridge During delayed ballistic reaches, motor areas consistently display movement-specific activity patterns prior to movement onset. It is…
• Dynamic layer-specific processing in the prefrontal cortex during working memory Humboldt-Universität zu Berlin The dorsolateral prefrontal cortex (dlPFC) is reliably engaged in working memory (WM) and comprises different cytoarchitectonic layers,…
• Robust characterisation of forest structure from airborne laser scanning—A systematic assessment and sample workflow for ecologists University of Bristol Abstract Forests display tremendous structural diversity, shaping carbon cycling, microclimates and terrestrial habitats. An important…
• The role of digital technologies in configuring circular ecosystems University of Cambridge Purpose This paper aims to explore the use of digital technologies in enabling circular ecosystems. We apply supply network (SN)…
• Advancements in dynamic characteristics analysis of superconducting electrodynamic suspension systems: Modeling, experiment, and optimization Tongji University • Review benefits and limits of simulation methods in superconducting EDS dynamics. • Discuss equivalent experimental methods for the…
• Multiscale Experiments and Predictive Modeling for Failure Mitigation in Additive Manufacturing of Lattices Marche Polytechnic University Abstract Additive Manufacturing (AM) empowers the creation of high‐performance cellular materials, underscoring the increasing need for…

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