"Build Your Own Internet of Things," a new online course developed at UC San Diego, has drawn the interest of more than 30,000 active users from around the world.
The nonprofit organization is based at the University of California San Diego’s Qualcomm Institute Innovation Space and has raised a total of $9.5 million since its creation in 2013, including grants, donations and contracts.
The global community of researchers, students, librarians, publishers, funders and scholars interested in the future of scholarship has announced the launch of its new annual Force 11 Scholarly Communications Institute, July 30-Aug. 4, 2017
A new proof-of-concept study by UC San Diego researchers succeeded in training computers to “learn” what a healthy versus an unhealthy gut microbiome looks like based on its genetic makeup.
Camille Nebeker, assistant professor of Family Medicine and Public Health at the University of California San Diego, will lead an effort to investigate whether federal regulations to protect human research participants are responsive to new forms of population health research, particularly studies that…
Experts at the recent Global Biological Standards Institute workshop — as well as Cell Press and Thermo Fisher Scientific — have agreed to adopt reproducibility standards first proposed by QI affiliate Anita Bandrowski and her colleagues.
KnuEdge and Calit2 workshop to focus on development of next-generation computing architectures to power machine learning.
Peter Otto, founding director of the Qualcomm Institute Sonic Arts Laboratory at the University of California San Diego, has joined the award-winning audio technology company Comhear, Inc. as Chief Science Officer.
It’s billed as “The Greatest Show (&Tell) on Earth,” and researchers from the University of California San Diego will once again be part of the spectacle as Maker Faire San Diego takes over Balboa Park.
Powerful new “brain-inspired” computing capabilities are turning the scientific method on its head by accelerating a “data science” experimental method that detects patterns in data before generating a hypothesis.