Is this the beginning of a smarter, faster, more inclusive AI future, or are we opening the door to problems we don’t fully ...

Traditionally, drug discovery relied heavily on trial and error, with long timelines and high costs. The introduction of ...

Carbon emissions continue to increase at record levels, fueling climate instability and worsening air quality conditions for ...

Severe weather events, such as heavy rainfall, are on the rise worldwide. Reliable assessments of these events can save lives ...

Data science merges statistics, science, computing, machine learning, and other domain expertise to generate meaningful insights from data, driving better decision-making and operational efficiency.

Sovereignty over your data and AI systems means having the architecture, observability, and human expertise to inspect, challenge, and contextualize machine-generated insights. This requires: ...

Data modeling is a critical component in the development of next-generation consumer electronics (CE), as it provides massive data support to implement smart services related to CE products, such as ...

A new scientific machine learning framework developed by Professors Horacio D. Espinosa, Sridhar Krishnaswamy, and collaborators accurately predicts and inversely designs the mechanical behavior of ...

Participants are expected to have a degree in economics, statistics, data science, or equivalent experience in data analysis and economic research-including understanding of macroeconomic concepts and ...

Government Science Data May Soon Be Hidden. They’re Racing to Copy It. Vast quantities of climate and environmental information have been removed from official websites in the past months.

Every field has its own standard for what data gets recorded for specimens archived in a museum collection, which can make research difficult.

Data science is a field of evidence seeking that combines data with domain information to generate new knowledge. The data science life cycle (DSLC) begins with a domain question or problem and ...