Researchers used SDSC's Comet supercomputer to better understand the wake effects of large floating wind farm arrays, which have become more prevalent in recent years.
Researchers at SDSC, LANL, and UNC Chapel Hill have developed a machine learning approach called transfer learning that lets them model novel materials by learning from data collected about millions of other compounds.
UC San Diego, UC Berkeley, and the University of Washington have been awarded a five-year, $5 million grant by the National Science Foundation (NSF) to develop CloudBank, a suite of managed services to simplify public cloud access for computer science research and education.
NJIT Mechanical and Industrial Engineering Professor Dibakar Datta and his team used the Comet supercomputer at the San Diego Supercomputer Center to create simulations of graphene-water interactions to see if graphene is a good candidate for delivering medicine to specific parts of the body.
Bladder cancer, one of the most common cancers in the U.S., may be soon helped by a novel non-invasive diagnostic method thanks to machine learning research by researchers at UC San Diego's San Diego Supercomputer Center and Moores Cancer Center.
UC San Diego mechanical and aerospace engineering graduate student Tao Wang recently demonstrated how an extremely strong magnetic field, similar to that on the surface of a neutron star, can be not only generated but also detected using an x-ray laser inside a solid material.
According to a release issued in April by Georgia Institute of Technology (Georgia Tech), a serendipitous discovery by graduate student Dylan T. Christiansen has led to materials that quickly change color from completely clear to a range of vibrant hues – and back again.
University of California and Princeton scientists have been collaborating on a computational astrophysics project to learn more about the recent discovery of a black hole which sits in the middle of a galaxy called Messier 87 (M87), approximately 55 million light years from Earth.
Using the Comet supercomputer at the San Diego Supercomputer Center (SDSC) at UC San Diego, campus researchers have demonstrated they can efficiently analyze more than 1,000 EEG 128-channel high-density data sets via the new Open EEGLAB Portal running on SDSC’s Neuroscience Gateway.