Most AI systems are trained on historical data. When conditions shift due to changing consumer sentiment, models trained on ...

In a recent article, researchers from the University of Jyväskylä, Finland, emphasize the importance of multiscale modeling of catalysis in understanding and developing (electro)chemical processes.

Penn researchers have developed a smarter AI method for solving notoriously difficult inverse equations, which help ...

Penn Engineers have developed a new way to use AI to solve inverse partial differential equations (PDEs), a particularly ...

Not only were CFD sims cheaper than wind tunnel time, but they were also much faster at iterating. Early design work is now ...

AI copilots are becoming essential study partners for STEM students, offering coding help, concept explanations, and project guidance directly within specialized tools like MATLAB and Simulink. These ...

Semiconductor engineering teams have long relied on an iterative simulation workflow: define the scenario, prepare the model, ...

Artificial intelligence systems based on neural networks—such as ChatGPT, Claude, DeepSeek or Gemini—are extraordinarily ...

Researchers based at Harvard Medical School and Beth Israel Deaconess Medical Center found that an AI reasoning model, ...

Hardware-in-the-loop (HIL) testing connects real controller hardware to a simulated environment, enabling engineers to verify systems safely and in real time before building physical prototypes. With ...

Model-based systems engineering (MBSE) has been around for a while, but it continues to gain ground in engineering projects ...

Explore mathematical economics—a method utilizing quantitative tools and models for economic theory analysis. Learn its ...