Networks of electronic information are embedded in nearly every aspect of our daily lives. From transportation and utility systems to telecommunication, everything from personal privacy to national security depends on maintaining the integrity of information in cyberspace.
As the Internet of Things expands, UC Davis computer security experts Matt Bishop and Sam King are looking for ways to checkmate hackers and intruders. (Getty Images)
UC Davis scientists are taking part in a project to build the new “Frontera” supercomputer at the University of Texas at Austin. Funded by a $60 million grant from the National Science Foundation announced last week, Frontera will be the fastest computer at any U.S. university and among the most powerful in the world.
Global simulation of Earth’s mantle convection by the NSF-funded Stampede supercomputer at UT Austin. Computational Infrastructure for Geodynamics, headquartered at UC Davis, is developing software for Earth sciences that will run on the new Frontera system. [Courtesy of ICES, UT Austin]
Digital information may appear to exist as abstract ones and zeroes, flipping effortlessly from one to another. But in fact there is a minimum amount of energy required to run any computation system, regardless of how “energy efficient” are its component parts. A recent paper from Jim Crutchfield and Alex Boyd at the UC Davis Complexity Sciences Center with Dibyendu Mandal at UC Berkeley shows that there is some inescapable friction, or “grit in the gears” between the levels of organization in an information system.
A UC Davis student team is one of eight teams worldwide recently selected to compete in Amazon’s 2018 Alexa Prize Challenge – an artificial intelligence competition to advance the technology behind the company’s popular social bot.
Team Gunrock includes 12 graduate students and two undergraduate students with diverse, interdisciplinary backgrounds related to artificial intelligence. Advised by Zhou Yu, an assistant professor of computer science in the College of Engineering, the team has received a $250,000 research stipend, Alexa-enabled devices and support from Amazon’s web services team to assist with their development efforts during the competition. The team also has access to Alexa’s application programming interfaces as well as additional tools, data and support from Amazon’s Alexa team.
What does the future of plant biology education and research look like? That’s the question on the mind of Siobhan Brady, associate professor of plant biology at UC Davis.
Big data approaches will be key to advances in plant biology, so students need to be trained in these areas. Unknown author/Wikipedia (CC BY 2.5)
In a Plant Physiology commentary paper, Brady, along with 37 other plant biologists from around the world, call for universities to integrate more quantitative and computational techniques into biology-oriented academic curricula. Introducing these skills early, the group advises, will help prepare tomorrow’s plant biologists for the next era of genomics research.
The Center for Integrated Computing and STEM Education at the University of California, Davis, has released version 4 of its popular C-STEM Studio software suite. In addition to free breakthrough tools for teaching math, coding, robotics and making, this major update includes expanded support with textbooks and curriculum for Lego Mindstorms NXT and EV3 robots, Raspberry Pi computers and Arduino control boards as well as Barobo Linkbots. These hardware platforms and related curriculum are seamlessly integrated in C-STEM Studio for learning math with hands-on physical computing and real-world projects.
C-STEM Studio is compatible with robots widely used in school classrooms.
As the Juno space probe approached Jupiter in June last year, researchers with the Computational Infrastructure for Geodynamics’ Dynamo Working Group were starting to run simulations of the giant planet’s magnetic field on one of the world’s fastest computers. While the timing was coincidental, the supercomputer modeling should help scientists interpret the data from Juno, and vice versa.
Video: Simulation of Jupiter’s magnetic fields
“Even with Juno, we’re not going to be able to get a great physical sampling of the turbulence occurring in Jupiter’s deep interior,” Jonathan Aurnou, a geophysics professor at UCLA who leads the geodynamo working group, said in an article for Argonne National Laboratory news. “Only a supercomputer can help get us under that lid.”
Jim Crutchfield wants to teach a machine to “see” in a new way, discovering patterns that evolve over time instead of recognizing patterns based on a stored template.
It sounds like an easy task – after all, any animal with basic vision can see a moving object, decide whether it is food or a threat and react accordingly, but what comes easily to a scallop is a challenge for the world’s biggest supercomputers.
CORI at Lawrence Berkeley Lab is one of the world’s fastest computers. It is named after Gerty Theresa Cori, the first woman to win a Nobel Prize for Physiology or Medicine. (NERSC/LBL photo)
2016 saw an unprecedented use of cyberattacks during a U.S. presidential election. According to the U.S. Department of Homeland Security and the Office of the Director of National Intelligence, the Russian government directed theft of emails and release of information in an apparent attempt to influence the election.
What does this mean for the coming year? I asked Professors Karl Levitt, Matt Bishop, Hao Chen, and Felix Wu of the UC Davis Computer Security Laboratory for some thoughts about cybersecurity in the wake of the 2016 election hack. Here’s what they had to say.
In the latest episode of the Three Minute Egghead podcast, Ilias Tagkopoulos talks about a computer model that predicts the metabolism of the bacteria Escherichia coli. While E. coli might be one of the most-studied organisms both in labs and as a cause of disease, there is still much we don’t know about it, he notes.
Tagkopoulos and his team spent two years pulling together all the data they could find on E. coli, from DNA sequences to metabolism, and assembling it into a single database. They then used computer clusters and the Blue Waters supercomputer to create their model. You can access their data here.