arXiv subjects

Matthew Smith

Publications and source records attributed to Matthew Smith.

At least 19 recordsLinked to original sources

arXiv2026

Building and Governing AI Systems: Advancing Social Workers' Roles across the Technology Industry, Human Service Organizations, and Policy Institutions

Artificial intelligence is moving the technology sector into domains social work has long served, including crisis response, mental health care, benefits administration, vocational rehabilitation, and child welfare. Social workers meet technology teams as users of their tools, as subjects in their datasets, and as first responders to what those systems deploy, yet they study these systems from outside the settings where the decisions are made. This paper introduces the standard roles on a technology product team and the decisions each one controls, reviews the disciplines around AI-era technology together with the social work scholarship that meets each, and identifies five groups of technology decision roles social workers can hold across the technology industry, human service organizations, and policy institutions, spanning product, governance, organizational technology leadership, grantee collaboration, and policy work. Product management is our primary example. We set the nine competencies of the 2022 Educational Policy and Accreditation Standards against the tasks that role performs to show where MSW training already teaches the method the job asks for. We then specify the technical understanding these roles require, extend the profession's technology ethics from use to deployment, and close with a research agenda for the profession's technology workforce.

cs.CY↗

arXiv2026

COSMOS-Web: Star formation along the early Hubble sequence and the evolution of dust over the redshift range 0<z<12

We have carried out a stacking analysis with the COSMOS-Web catalogue on one of the deepest ever SCUBA-2 images at 850 microns, allowing us to estimate the mean submillimetre flux density for samples of galaxies split by stellar mass and morphological class over the redshift range 0 ~80 solar masses per year at 2 < z < 4.5. In this redshift range, the mean star-formation rate for these galaxies falls along the Hubble sequence from ~280 solar masses per year for irregular galaxies at one end to ~80 solar masses per year for spheroids at the other end, which shows that quenching was already happening shortly after the emergence of the Hubble sequence. The decrease in the star-formation rate for the spheroidal galaxies can be reproduced with a `starvation' quenching model with a depletion time of ~10^{8.2} years. We also show that the transformation of `submillimetre galaxies' can reproduce the growth in number-density of massive bulge-dominated and spheroidal galaxies over the redshift range 1.5 <z < 4. As a side-project, we have used our stacking results to show that the ratio of dust mass to stellar mass in galaxies increases with redshift out to z~8 and to determine the relationship between the mean density of dust and redshift in the range 0 < z <12. We show that a chemical evolution model based on the `star-formation history' of the universe, with a gas outflow rate equal to the star-formation rate, can explain the monotonic rise in the dust-to-stellar mass ratio and reproduce the relationship between mean dust density and redshift remarkably accurately.

astro-ph.GA↗

arXiv2025

The SPace-based InterFerometer Feasibility (SPIFF) Project: Enabling Future High-Resolution Astronomy Across the EM Spectrum

A plethora of astronomical science cases can only be achieved with high angular resolution observations, and we can expect the number of these to grow as astronomers are constrained by the size limitations of single-aperture space telescopes, making space-based interferometry inevitable. However, the enabling technologies do not have flight heritage at the system level, and the concept remains immature to much of the community, meaning no direct-detection synthetic-aperture space-based interferometer has yet flown and an opportunity exists for the UK to take a world leading role. Here we propose the SPace-based InterFerometry Feasibility (SPIFF) Project as a program to address both issues simultaneously by: 1) completing a thorough survey of the science cases across the EM spectrum that would directly benefit from, or be impossible without, space-based interferometry; 2) down selecting key requirements via a Science Traceability Matrix mapping exercise; 3) host a workshop for the UK astronomical community to consolidate these findings; 4) build a technology demonstration mission to raise TRL and achieve flight heritage of critical technologies. Such a program positions the UK as the partner of choice for any future NASA or ESA space-based interferometry mission, allowing the UK to lead groundbreaking scientific discoveries, while also directly benefiting the UK industrial base by advancing domestic exportable technologies and building direct synergy with other UK space priorities. Indeed, the UK is uniquely positioned to lead in space-based interferometry, possessing a rare trifecta of domestic strengths: world-class expertise in ground-based interferometry and space-based instrumentation; commercial entities developing mission-critical technologies; and scientists whose research spans the full range of science cases that would benefit directly from space-based interferometry.

astro-ph.IM↗

arXiv2025

The Role of Risk Modeling in Advanced AI Risk Management

Rapidly advancing artificial intelligence (AI) systems introduce novel, uncertain, and potentially catastrophic risks. Managing these risks requires a mature risk-management infrastructure whose cornerstone is rigorous risk modeling. We conceptualize AI risk modeling as the tight integration of (i) scenario building$-$causal mapping from hazards to harms$-$and (ii) risk estimation$-$quantifying the likelihood and severity of each pathway. We review classical techniques such as Fault and Event Tree Analyses, FMEA/FMECA, STPA and Bayesian networks, and show how they can be adapted to advanced AI. A survey of emerging academic and industry efforts reveals fragmentation: capability benchmarks, safety cases, and partial quantitative studies are valuable but insufficient when divorced from comprehensive causal scenarios. Comparing the nuclear, aviation, cybersecurity, financial, and submarine domains, we observe that every sector combines deterministic guarantees for unacceptable events with probabilistic assessments of the broader risk landscape. We argue that advanced-AI governance should adopt a similar dual approach and that verifiable, provably-safe AI architectures are urgently needed to supply deterministic evidence where current models are the result of opaque end-to-end optimization procedures rather than specified by hand. In one potential governance-ready framework, developers conduct iterative risk modeling and regulators compare the results with predefined societal risk tolerance thresholds. The paper provides both a methodological blueprint and opens a discussion on the best way to embed sound risk modeling at the heart of advanced-AI risk management.

cs.CY↗

arXiv2025

Toward Quantitative Modeling of Cybersecurity Risks Due to AI Misuse

Advanced AI systems offer substantial benefits but also introduce risks. In 2025, AI-enabled cyber offense has emerged as a concrete example. This technical report applies a quantitative risk modeling methodology (described in full in a companion paper) to this domain. We develop nine detailed cyber risk models that allow analyzing AI uplift as a function of AI benchmark performance. Each model decomposes attacks into steps using the MITRE ATT&CK framework and estimates how AI affects the number of attackers, attack frequency, probability of success, and resulting harm to determine different types of uplift. To produce these estimates with associated uncertainty, we employ both human experts, via a Delphi study, as well as LLM-based simulated experts, both mapping benchmark scores (from Cybench and BountyBench) to risk model factors. Individual estimates are aggregated through Monte Carlo simulation. The results indicate systematic uplift in attack efficacy, speed, and target reach, with different mechanisms of uplift across risk models. We aim for our quantitative risk modeling to fulfill several aims: to help cybersecurity teams prioritize mitigations, AI evaluators design benchmarks, AI developers make more informed deployment decisions, and policymakers obtain information to set risk thresholds. Similar goals drove the shift from qualitative to quantitative assessment over time in other high-risk industries, such as nuclear power. We propose this methodology and initial application attempt as a step in that direction for AI risk management. While our estimates carry significant uncertainty, publishing detailed quantified results can enable experts to pinpoint exactly where they disagree. This helps to collectively refine estimates, something that cannot be done with qualitative assessments alone.

cs.CY↗

arXiv2025

Real-time Cricket Sorting By Sex

The global demand for sustainable protein sources is driving increasing interest in edible insects, with Acheta domesticus (house cricket) identified as one of the most suitable species for industrial production. Current farming practices typically rear crickets in mixed-sex populations without automated sex sorting, despite potential benefits such as selective breeding, optimized reproduction ratios, and nutritional differentiation. This work presents a low-cost, real-time system for automated sex-based sorting of Acheta domesticus, combining computer vision and physical actuation. The device integrates a Raspberry Pi 5 with the official Raspberry AI Camera and a custom YOLOv8 nano object detection model, together with a servo-actuated sorting arm. The model reached a mean Average Precision at IoU 0.5 (mAP@0.5) of 0.977 during testing, and real-world experiments with groups of crickets achieved an overall sorting accuracy of 86.8%. These results demonstrate the feasibility of deploying lightweight deep learning models on resource-constrained devices for insect farming applications, offering a practical solution to improve efficiency and sustainability in cricket production.

cs.CV↗

arXiv2025

Influence Dynamics and Stagewise Data Attribution

Current training data attribution (TDA) methods treat the influence one sample has on another as static, but neural networks learn in distinct stages that exhibit changing patterns of influence. In this work, we introduce a framework for stagewise data attribution grounded in singular learning theory. We predict that influence can change non-monotonically, including sign flips and sharp peaks at developmental transitions. We first validate these predictions analytically and empirically in a toy model, showing that dynamic shifts in influence directly map to the model's progressive learning of a semantic hierarchy. Finally, we demonstrate these phenomena at scale in language models, where token-level influence changes align with known developmental stages.

cs.LG↗

arXiv2025

The PRIMA promise of deciphering interstellar dust evolution with observations of the nearby Universe

This paper develops a few science cases, using the PRIMA far-IR probe, aimed at achieving several breakthroughs in our understanding of the dust properties and their evolution. We argue that the specific observational capabilities of PRIMA, namely its unprecedented sensitivity over the whole far-IR range and the possibility to obtain continuous spectra between wavelengths 24 and 235 microns, are essential to progress in our understanding of the physics of the interstellar medium and galaxy evolution. Our science cases revolve around observations of nearby galaxies. We discuss the importance of detecting the IR emission of the diffuse interstellar medium of these galaxies, including very low-metallicity systems. We also discuss the opportunity of detecting various solid-state features to understand the mineralogy of interstellar grains. Finally, we stress the unique opportunity brought by the possible simultaneous measures of both the dust continuum and the far-IR fine-structure gas lines. These science cases could be distributed in a few large programs.

astro-ph.IM↗

arXiv2025

Toward an African Agenda for AI Safety

This paper maps Africa's distinctive AI risk profile, from deepfake fuelled electoral interference and data colonial dependency to compute scarcity, labour disruption and disproportionate exposure to climate driven environmental costs. While major benefits are promised to accrue, the availability, development and adoption of AI also mean that African people and countries face particular AI safety risks, from large scale labour market disruptions to the nefarious use of AI to manipulate public opinion. To date, African perspectives have not been meaningfully integrated into global debates and processes regarding AI safety, leaving African stakeholders with limited influence over the emerging global AI safety governance agenda. While there are Computer Incident Response Teams on the continent, none hosts a dedicated AI Safety Institute or office. We propose a five-point action plan centred on (i) a policy approach that foregrounds the protection of the human rights of those most vulnerable to experiencing the harmful socio-economic effects of AI; (ii) the establishment of an African AI Safety Institute; (iii) promote public AI literacy and awareness; (iv) development of early warning system with inclusive benchmark suites for 25+ African languages; and (v) an annual AU-level AI Safety & Security Forum.

cs.CY↗

arXiv2025

Bulk Ferroelectric Heterostructures for High Temperature Lead-Free Piezoelectrics

Remarkable exploitation of valence and lattice mismatch in epitaxial ferroelectric heterostructures generates physical effects not classically expected for perovskite oxides, such as 2D electron gas and polar skyrmions. However the widespread application of these interfacial properties and functionalities is impeded by the ultrathin layered structure and essential presence of underlying lattice-matched substrates for the deposition of epitaxial thin films. Here, we report a bottom-up pathway to synthesize bulk ferroelectric heterostructures (BFH) with periodic composition fluctuation (8 nm in wavelength) using elemental partitioning by cation diffusion, providing opportunities to exploit novel characteristics of hetero-epitaxial oxide thin films in bulk materials. Exemplar monolithic BiFeO3-BaTiO3 BFH ceramics described herein share common features with their thin film heterostructure counterparts, which facilitates control and stabilisation of ferroelectric polarisation along with a significant enhancement in Curie temperature, Tc, and functionality. BFH ceramics exhibit a record Tc (up to 824 {\deg}C) and a piezoelectric coefficient (d33 = 115 pC N-1 ), in comparison with other perovskite or non-perovskite solid solutions, providing sustainable solutions for emergent high temperature piezoelectric sensing, actuation and energy conversion applications. By creating BFH ceramics using different electromechanical boundary conditions, distinct morphologies of aliovalent A-site cation segregated regions along with different types of ferroelectric order are achieved. This formation mechanism provides unprecedented control over local ferroelectric ordering and domain stabilisation in BFH ceramics; it also paves the way to explore new types of functionality, beyond those achievable in both bulk ferroelectrics and thin film heterostructures.

cond-mat.mtrl-sci↗

arXiv2025

The Optical Design of the Carbon Investigation(Carbon-I) Imaging Spectrometer

The proposed Carbon Investigation (Carbon-I) Imaging Spectrometer is designed to measure variations of greenhouse gases in Earth's atmosphere. The instrument will survey the Earth from its own spacecraft at an altitude of approximately 610 km. It will use a coarse ground sampling distance (GSD) of <400 m in global mode for land and coastal monitoring and finer 35 m GSD in target mode to sample key regions. The identification and quantification of greenhouse gases require continuous spectral sampling over the 2040-2380 nm wavelength range with <1 nm spectral sampling. The proposed design builds upon Jet Propulsion Laboratory's (JPL) experience of spaceflight Dyson imaging spectrometers to achieve spectral sampling of 0.7 nm per pixel. This paper presents the proposed Carbon-I optical design comprised of a freeform three-mirror anastigmat telescope that couples to a F/2.2, highly uniform Dyson-inspired imaging spectrometer. The high uniformity and throughput enables Carbon-I to measure Earth's greenhouse gas concentrations with unprecedented precision and spatial sampling.

physics.optics↗

arXiv2025

Dynamics of single Au nanoparticles on graphene simultaneously in real- and diffraction space by time-series convergent beam electron diffraction

Convergent beam electron diffraction (CBED) on two-dimensional materials allows simultaneous recording of the real-space image (tens of nanometers in size) and diffraction pattern of the same sample in one single-shot intensity measurement. In this study, we employ time-series CBED to visualize single Au nanoparticles deposited on graphene. The real-space image of the probed region, with the amount, size, and positions of single Au nanoparticles, is directly observed in the zero-order CBED disk, while the atomic arrangement of the Au nanoparticles is available from the intensity distributions in the higher-order CBED disks. From the time-series CBED patterns, the movement of a single Au nanoparticle with rotation up to 4{\deg} was recorded. We also observed facet diffraction lines - intense bright lines formed between the CBED disks of the Au nanoparticle, which we explain by diffraction at the Au nanoparticle's facets. This work showcases CBED as a useful technique for studying adsorbates on graphene using Au nanoparticles as a model platform, and paves the way for future studies of different objects deposited on graphene.

cond-mat.other↗

arXiv2025

3D Nephrographic Image Synthesis in CT Urography with the Diffusion Model and Swin Transformer

Purpose: This study aims to develop and validate a method for synthesizing 3D nephrographic phase images in CT urography (CTU) examinations using a diffusion model integrated with a Swin Transformer-based deep learning approach. Materials and Methods: This retrospective study was approved by the local Institutional Review Board. A dataset comprising 327 patients who underwent three-phase CTU (mean $\pm$ SD age, 63 $\pm$ 15 years; 174 males, 153 females) was curated for deep learning model development. The three phases for each patient were aligned with an affine registration algorithm. A custom deep learning model coined dsSNICT (diffusion model with a Swin transformer for synthetic nephrographic phase images in CT) was developed and implemented to synthesize the nephrographic images. Performance was assessed using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Absolute Error (MAE), and Fr\'{e}chet Video Distance (FVD). Qualitative evaluation by two fellowship-trained abdominal radiologists was performed. Results: The synthetic nephrographic images generated by our proposed approach achieved high PSNR (26.3 $\pm$ 4.4 dB), SSIM (0.84 $\pm$ 0.069), MAE (12.74 $\pm$ 5.22 HU), and FVD (1323). Two radiologists provided average scores of 3.5 for real images and 3.4 for synthetic images (P-value = 0.5) on a Likert scale of 1-5, indicating that our synthetic images closely resemble real images. Conclusion: The proposed approach effectively synthesizes high-quality 3D nephrographic phase images. This model can be used to reduce radiation dose in CTU by 33.3\% without compromising image quality, which thereby enhances the safety and diagnostic utility of CT urography.

cs.CV↗

arXiv2025

An Integral Field Unit for the Binospec Spectrograph

Binospec is a wide-field optical (360 to 1000 nm) spectrograph commissioned at the MMT 6.5m telescope in 2017. In direct imaging mode Binospec addresses twin 8$^\prime$ (wide) by 15$^\prime$ (slit length) fields of view. We describe an optical fiber based integral field unit (IFU) that remaps a 12$^{\prime\prime}$ x 16$^{\prime\prime}$ contiguous region onto two pseudo slits, one in each Binospec channel. The IFU, commissioned in 2023, fits into the space of a standard slit mask frame and can be deployed as desired in a mixed program of slit masks, long slits, and IFU observations. The IFU fibers are illuminated by a hexagonal lenslet array with a 0.6$^{\prime\prime}$ pitch. A separate bundle of sky fibers consists of close-packed bare fibers arranged within an 11.8$^{\prime\prime}$ circular aperture. The 640 IFU fibers and 80 sky fibers have a core diameter of 150$\mu$m, corresponding to 0.90$^{\prime\prime}$. Three gratings are available, 270lpm with R$\sim$2000, 600lpm with R$\sim$5300, and 1000 lpm with R$\sim$6000.

astro-ph.IM↗

arXiv2024

Deep Generative Classification of Blood Cell Morphology

Accurate classification of haematological cells is critical for diagnosing blood disorders, but presents significant challenges for machine automation owing to the complexity of cell morphology, heterogeneities of biological, pathological, and imaging characteristics, and the imbalance of cell type frequencies. We introduce CytoDiffusion, a diffusion-based classifier that effectively models blood cell morphology, combining accurate classification with robust anomaly detection, resistance to distributional shifts, interpretability, data efficiency, and superhuman uncertainty quantification. Our approach outperforms state-of-the-art discriminative models in anomaly detection (AUC 0.990 vs. 0.918), resistance to domain shifts (85.85% vs. 74.38% balanced accuracy), and performance in low-data regimes (95.88% vs. 94.95% balanced accuracy). Notably, our model generates synthetic blood cell images that are nearly indistinguishable from real images, as demonstrated by an authenticity test in which expert haematologists achieved only 52.3% accuracy (95% CI: [50.5%, 54.2%]) in distinguishing real from generated images. Furthermore, we enhance model explainability through the generation of directly interpretable counterfactual heatmaps. Our comprehensive evaluation framework, encompassing these multiple performance dimensions, establishes a new benchmark for medical image analysis in haematology, ultimately enabling improved diagnostic accuracy in clinical settings. Our code is available at https://github.com/CambridgeCIA/CytoDiffusion.

cs.CV↗

arXiv2024

Off-axis Hartmann wavefront sensing for the GMT-Consortium Large Earth Finder (G-CLEF) red camera optics

The Hartmann test is a method used to measure the wavefront error in a focal optical system, wherein a mask with a pattern of small holes is placed at the system's aperture stop. By taking an image at a defocused plane, the differences between the ideal and real positions of the reimaged holes (called the transverse ray aberrations) can be measured, which can then be used to estimate the wavefront error. However, the Hartmann test is usually used with an on-axis field. In this paper, we present a wavefront sensing method which generalizes the classical Hartmann test for off-axis field angles and arbitrary reference wavefronts. Our method involves taking images at two defocused planes, and then using the real reimaged hole positions on both planes to estimate the trajectories of rays from the system's exit pupil, at which the reference wavefront is situated. We then propagate the rays forward from the reference wavefront to one of the two defocused planes, in order to find the ideal reimaged hole positions, from which we can compute transverse ray aberrations. We derive and solve a pair of nonlinear partial differential equations relating transverse ray aberrations to wavefront error, using Zernike decomposition and nonlinear least squares. Our method has been verified on simulated data from the 7-lens f/2.25 red camera system of the GMT-Consortium Large Earth Finder (G-CLEF), a high resolution optical echelle spectrograph which will be a first light instrument for the Giant Magellan Telescope (GMT).

astro-ph.IM↗

arXiv2024

Maritime Tracking Data Analysis and Integration with AISdb

Efficiently handling Automatic Identification System (AIS) data is vital for enhancing maritime safety and navigation, yet is hindered by the system's high volume and error-prone datasets. This paper introduces the Automatic Identification System Database (AISdb), a novel tool designed to address the challenges of processing and analyzing AIS data. AISdb is a comprehensive, open-source platform that enables the integration of AIS data with environmental datasets, thus enriching analyses of vessel movements and their environmental impacts. By facilitating AIS data collection, cleaning, and spatio-temporal querying, AISdb significantly advances AIS data research. Utilizing AIS data from various sources, AISdb demonstrates improved handling and analysis of vessel information, contributing to enhancing maritime safety, security, and environmental sustainability efforts.

cs.DB↗

arXiv2024

The key science drivers for the Atacama Large Aperture Submillimeter Telescope (AtLAST)

Sub-mm and mm wavelengths provide a unique view of the Universe, from the gas and dust that fills and surrounds galaxies to the chromosphere of our own Sun. Current single-dish facilities have presented a tantalising view of the brightest (sub-)mm sources, and interferometers have provided the exquisite resolution necessary to analyse the details in small fields, but there are still many open questions that cannot be answered with current facilities: Where are all the baryons? How do structures interact with their environments? What does the time-varying (sub-)mm sky look like? In order to make major advances on these questions and others, what is needed now is a facility capable of rapidly mapping the sky spatially, spectrally, and temporally, which can only be done by a high throughput, single-dish observatory. An extensive design study for this new facility is currently being undertaken. In this paper, we focus on the key science drivers and the requirements they place on the observatory. As a 50m single dish telescope with a 1-2{\deg} field of view, the strength of the Atacama Large Aperture Submillimeter Telescope (AtLAST) is in science where a large field of view, highly multiplexed instrumentation and sensitivity to faint large-scale structure is important. AtLAST aims to be a sustainable, upgradeable, multipurpose facility that will deliver orders of magnitude increases in sensitivity and mapping speeds over current and planned telescopes.

astro-ph.IM↗