This paper presents EurekAgent, an environment-engineered agent system for metric-driven autonomous scientific discovery.

The paper introduces PetroBench, a comprehensive benchmark for evaluating Large Language Models across various domains of petroleum engineering, finding that models perform better on subjective tasks…

The paper introduces a U-Net deep learning surrogate model to accelerate Quality-Diversity optimization for urban layout design, demonstrating that this spatial approach enables highly accurate climat…

The paper introduces an integrated platform combining BIM, sensor data, and advanced algorithms to significantly optimize energy consumption in green building design, achieving a 29.3% reduction in en…

The study developed a comprehensive model to assess how hydrogen embrittlement affects pipeline defects, finding that hydrogen generally does not increase damage severity unless a passive dent is comb…

This perspective reviews advanced design principles for Metal-Organic Frameworks (MOFs) used in water harvesting and details how integrating Artificial Intelligence (AI) can accelerate the discovery o…

This paper proposes an automated method to generate complete PDDL planning problems directly from Asset Administration Shell (AAS) capability models, eliminating the need for specialized planning expe…

The paper introduces SPARROW, an autonomous, open-source platform that uses solar power, edge AI, and satellite communication to enable continuous, scalable biodiversity monitoring in remote global ec…

The paper introduces CEON, a Circular Economy Ontology Network, designed to improve semantic interoperability and knowledge representation across diverse industry sectors throughout the product life c…

This paper investigates the thermal constraints of deploying AI compute infrastructure in space, comparing GPUs and compute-in-memory (CIM) accelerators using a co-design methodology.

This paper analyzes the information security practices of Ugandan climate activists protesting the EACOP, finding that their daily lives are shaped by autonomous, multi-layered tactics designed to mit…

This paper provides the first comprehensive threat model for IoT-enabled Controlled Environment Agriculture (CEA) systems, identifying 123 unique threats and proposing a defense-in-depth framework to…

This paper details the design and evolution of a Hardware Reverse Engineering (HRE) course, providing key lessons for educators teaching rapidly changing technical domains.

FLORO is a multimodal geospatial foundation model that learns transferable remote sensing representations from a small, diverse corpus, achieving strong performance across various sensor types and res…

The paper introduces an LLM-driven framework to automatically standardize, structure, and enrich unstructured free-text wind turbine maintenance logs, transforming qualitative field observations into…

ImmersiveTTS is an environment-aware text-to-speech model that generates natural speech seamlessly integrated within environmental contexts by explicitly modeling cross-modal interactions, achieving s…

The paper adapts and evaluates two machine learning models, ArchesWeather and ArchesWeatherGen, demonstrating that when forced with boundary conditions, they can produce stable, long-term climate simu…

This paper synthesizes expert knowledge from a workshop to provide a comprehensive framework and best-practice guidelines for developing high-quality reinforcement learning environments for autonomous…

This paper introduces ASE-26, a comprehensive undergraduate curriculum designed to formalize and teach agentic software engineering as a distinct academic discipline.

This paper investigates the robustness of world models in vision-based quadrotor navigation and identifies factors governing their quality.