Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...

To prevent algorithmic bias, the authors call for multivariable modeling frameworks that jointly incorporate biological sex, genetic ancestry, and gender-related life-course exposures.

In 2026, the global AI landscape has shifted from experimental pilots to "infrastructure-grade" deployment, a transition led by systems architects like Anand Chauhan. While 55% of organizations use AI ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Companies ranging from OpenAI, Meta, Microsoft, and Google to smaller firms and startups are looking for high-quality AI ...

A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

As a national leader in applied technology education, Pennsylvania College of Technology is built for a global economy driven ...