A team led by Daniela Ushizima of the Computational Research Division has built a Python-based tool for content-based image retrieval (CBIR) capable of searching relevant items from large datasets, given unseen samples. Named “pyCBIR,” the tool can be used to catalog and retrieve images from different science domains, such as biology, materials research and geology.
Rare Supernova Ushers in New Era for Cosmology
NWChem’s Planewave Now “Purring” on KNL Nodes
Lin Lin Awarded 2017 SIAG/CSE Early Career Prize
Catching Extreme Waves with High-Resolution Modeling
Scott Beamer, a post-doc in the Computational Research Division’s Computer Architecture Group, is to receive the 2016 SPEC Kaivalya Dixit Distinguished Dissertation Award at the 8th ACM/SPEC International Conference on Performance Engineering being held April 22-27 in L’Aquila, Italy.
Using an automated supernova-hunting pipeline based at NERSC, astronomers have captured multiple images of a gravitationally lensed Type Ia supernova. This detection is currently the only one of its kind, but astronomers believe that if they can find more, they may be able to measure the rate of the universe’s expansion within four percent accuracy. Fortunately, two Berkeley Lab researchers have a method for identifying more of these events using existing wide-field surveys.
Berkeley Lab Computing Sciences-sponsored summer student Jessica Hatcher won a first place award for her research poster “Quantitative Structure Activity Relationships (QSAR) for Biological Effects of Synthetic Cathinones” at the 74th Joint Annual Meeting of The National Institute of Science/ Beta Kappa Chi. Hatcher was mentored by CRD's Bert de Jong last summer.