Artificial Intelligence

Hammer of justice strikes down on AI, for ethical AI

Governance For Ethical AI

Artificial Intelligence, Computer Science / Leave a Comment

Integrating Trustworthiness, Lifecycle Stages, and Stakeholder Roles: A Framework for Addressing AI’s Data-Driven Challenges and Ensuring Ethical Deployment with Actionable Insights for Risk Mitigation and Regulatory Compliance Across Sectors Challenges in AI Governance and Their Significance Artificial intelligence systems have advanced beyond prototypes to support essential functions in sectors such as finance, healthcare, and logistics. […]

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Why Are Some Watersheds More Sediment-Productive Than Others? An Explainable AI Approach

Artificial Intelligence, Civil Engineering, Computer Science, Data Science, Geomatics, MSc Thesis / Leave a Comment

High-frequency turbidity sensors from 134 USGS stations, paired with RUSLE erosion estimates and explainable random forest models, map sediment yield and delivery ratios across the contiguous United States, revealing that human-modified landscapes dominate sediment transport efficiency while natural factors control total production, and highlighting priority sub-basins for targeted management in the Upper Mississippi and Chesapeake

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Machine Learning for Iceberg Stability: Ground Imagery and Logistic Regression Offer New Practical Insights

Artificial Intelligence, Computer Science, Data Science, Engineering, Geomatics, MSc Thesis / Leave a Comment

Analyzing thousands of icebergs captured in time-lapse footage from Alaska and Greenland, this research demonstrates that logistic regression applied to visible width and height can help estimate the probability of instability providing engineers with a foundational, field-derived method for assessing capsize risk in Arctic coastal environments. The Challenge of Iceberg Capsize in Arctic Waters Iceberg

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Bidirectional LSTM Networks Enable High-Resolution Railway Track Stiffness Monitoring from Drive-By Vibrations

Artificial Intelligence, Civil Engineering, Infrastructure, Mechanical Engineering / Leave a Comment

TU Delft researchers present an LSTM-BiLSTM architecture that combines sleeper-level framing of axle-box acceleration signals with LSTM-based temporal feature extraction and bidirectional processing to deliver accurate, simultaneous estimation of railpad and ballast stiffness at individual sleeper resolution — even under realistic measurement noise. The Critical Need for Accurate Track Stiffness Monitoring Railway track stiffness is

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Machine Learning Meets Soil Dynamics

Artificial Intelligence, Computer Science, Data Science, Engineering, Geomatics, Journal publication / Leave a Comment

A data-driven review shows how modern machine-learning models consistently outperform traditional empirical equations in predicting soil shear modulus and damping ratio, offering geotechnical engineers a clearer, more efficient path to characterizing dynamic soil behavior while highlighting practical limitations, data requirements, and future research needs. Why Soil Dynamics Still Challenge Engineers Accurate characterization of soil dynamic

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Advancing 3D Land Administration with Point Clouds

Artificial Intelligence, Computer Science, Data Science, Engineering, Geomatics, Journal publication / Leave a Comment

Discover how researchers are transforming urban land administration by integrating cadastral floor plans with nationwide airborne LiDAR to create detailed 3D point clouds, offering a cost-effective alternative to BIM for visualizing legal property boundaries in complex vertical structures—paving the way for scalable digital twins. The Challenge of Vertical Urbanization in Land Administration Urban areas are

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PACMANN: Smarter Point Placement for AI-Based PDE Solvers

Artificial Intelligence, Computer Science, Data Science, Journal publication / Leave a Comment

A gradient guided adaptive sampling method that repositions collocation points to reduce computational cost, improve stability, and help physics informed neural networks handle complex, high dimensional PDE simulations more efficiently, making advanced scientific machine learning more practical for real engineering analysis and design workflows today. Why Engineers Should Care Partial differential equations (PDEs) underpin much

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Shanghai’s 30-Year Land Subsidence Evolution

Artificial Intelligence, Computer Science, Data Science, Engineering, Geomatics, Journal publication / Leave a Comment

Dive into Shanghai’s sinking secrets: This study fuses 30 years of multi-sensor satellite data with AI modeling to map subsidence shifts from urban cores to coastal zones, revealing how groundwater management curbs rates and offers strategies for flood-resilient cities. The Subsidence Challenge Land subsidence in coastal megacities like Shanghai endangers infrastructure, increases flood risks, and

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Advancing Road Inspections with Drones and AI

Artificial Intelligence, Civil Engineering, Data Science, Engineering, Infrastructure, Journal publication / Leave a Comment

What if engineers could scan entire road networks from the air and spot damage early, quickly, and safely? With drones and AI working together, pavement inspection is beginning to move from boots on the ground to intelligence in the sky. Here’s how UAV imagery and the YOLOv7 deep learning model support faster, safer, and more

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AI for Wild Weather Swings; Challenges and Solutions

Artificial Intelligence, Computer Science, Data Science, Geomatics, Journal publication / Leave a Comment

This research pushes boundaries by fusing AI’s knack for spotting nonlinear links in massive datasets with the solid physics of climate models, proving we can boost reliable forecasts of extreme event stats—like how often or how bad they get—over subseasonal to decadal horizons. Why Forecasting Climate Extremes Matters In our warming world, ramped-up extremes like

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