Data science was born centuries ago when vast amounts of astronomical data first became available. To draw actionable conclusions from the information, new approaches for analyzing data had to be ...

Four physicists share their journeys through academia into industry and offer words of wisdom for those considering making a similar move. Throughout his higher education, Jamie Antonelli had always ...

In a recent perspective published in Nature, Lawrence Livermore National Laboratory (LLNL) scientists and international collaborators outline key challenges and future directions in using machine ...

High Energy Physics (HEP) is a deeply collaborative and software-driven discipline, where scientific discovery depends on advanced computing, data analysis, ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

It seems like everyone wants a piece of Lu Lu’s research. Biologists. Physicians. Astronomers. Climatologists. Physicists. Chemists. Materials scientists. The federal government. Even the occasional ...

The simulation of high-energy particle collisions is an essential task in high-energy nuclear and particle physics and high-energy astroparticle physics. However, although data sets from both fields ...

Data analysis and machine learning are finding applications in many fields of fundamental sciences, and theoretical physics is no exception. My group at the Institut de Physique Théorique (IPhT) ...

Condensed-matter physics and materials science have a silo problem. Although researchers in these fields have access to vast amounts of data – from experimental records of crystal structures and ...

Messenger from the dark side: Dark matter may interact with normal matter via a hypothetical particle known as a dark photon. (Courtesy: Shutterstock/80's Child) A new analysis conducted by an ...