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.
By Linda Vu, Lawrence Berkeley National Laboratory
Getting a better picture of connections between brain areas is the goal of a new tool developed by researchers at the U.S. Department of Energy’s Lawrence Berkeley National Laboratory and UC Davis. Their “Brain Modulyzer” software allows researchers to visualize and explore brain activity, either while a subject is performing tasks or at rest.
We’re adding a new element to the Egghead blog this month with Three Minute Egghead, a podcast about research at UC Davis. While we figure out a few details about RSS feeds and XML, I’ll be posting these audio files to the Egghead blog, usually with an accompanying blog post.
Our first piece is about two UC Davis computer scientists who are using data from the open-source programming website GitHub to learn about coder’s work habits and in particular, how multitasking affects productivity.
Study author Bogdan Vasilescu will be presenting the study at the International Conference on Software Engineering in Austin, Texas tomorrow, May 20.
Audio: Listen to a version of this story on the Three Minute Egghead podcast.
How many projects can you work on at the same time, before losing efficiency? There are many reasons to get involved in multiple projects – impress your boss, gain personal satisfaction, help out colleagues or just because you’re interested. But at some point, there must be one project too many.
“There is a limit,” said Bogdan Vasilescu, postdoctoral researcher in the DECAL lab at the UC Davis Department of Computer Science. “Multitasking fills time that’s otherwise unused, but there is a limit at four or five projects in a week.”
Within just a few years, we’ve got used to controlling devices by swiping, scrolling or tapping our fingers on a touch screen. But soon you might not even have to touch anything at all to check your email or play a video – just wave your hand in the air, thanks to ultrasonic technology from Chirp Microsystems, a startup company founded in 2013 by researchers from UC Davis and UC Berkeley.
Chirp’s technology is “disruptive” in the ultrasound area, said David Horsley, professor of electrical and computer engineering at UC Davis and co-founder of the company. Chirp’s ultrasound transducers are smaller and operate with much lower power needs than any currently available.
A team of researchers from the University of California, Davis and the University of Washington have demonstrated that the conductance of DNA can be modulated by controlling its structure, thus opening up the possibility of DNA’s future use as an electromechanical switch for nanoscale computing. Although DNA is commonly known for its biological role as the molecule of life, it has recently garnered significant interest for use as a nanoscale material for a wide-variety of applications.
Big Data has a problem right now. We produce an avalanche of information every day by just walking around with our smartphones or posting on social media. Researchers in the social sciences today are collaborating across disciplines to turn this wealth of information into knowledge.
Martin Hilbert, an assistant professor of communication at UC Davis, is developing new ways to think about how social scientists can use this data to understand societies. In this Q&A, he discusses what Big Data and living in an information society could mean for our social evolution.
“There’s this big debate whether an author leaves a quantitative fingerprint on his or her work. It could be from things like average sentence length or how many adverbs you include in your writing or your speech,” Aranovich said.