A boost from the Legislature — plus grants from the likes of Amazon.com — is increasing the size the University of Washington’s computer science program by 25 percent this year.
That includes an increase of undergraduates being accepted to the program from about 160 a year to 200 a year, according to Hank Levy, chairman of the Computer Science and Engineering Department.
Levy and other faculty provided the update during the school’s annual Industrial Affiliates meeting with tech companies and investors who support the program and recruit its graduates.
The school also has successfullyh recruited top-tier faculty, including world experts in machine learning, and more hires are in the works.
“We’ve had really the most remarkable year in our history,” Levy said. “Not only did we hire a lot of people, we hired phenomenal people.”
The state shifted nearly $8 million to boost engineering programs at the UW and Washington State University this year, providing $3.8 million for each school.
Levy said the UW computer science program requested $1.8 million of that funding and received $1.6 million. It’s hoping to receive an additional $1 million in funds that will come from having so many additional students in the program.
In addition to boosting undergraduate enrollment, the department is adding 50 new Ph.D. students — twice as many as last year, he said. Also doubling is the number of students in the fifth year master’s program, which is growing from 10 to 20 students per year.
The event included recruiting sessions and research presentations in areas such as wireless power, human-computer interaction and privacy.
A lunchtime lecture was given by Carlos Guestrin, a machine-learning professor that the UW lured from Carnegie Mellon University with a $1 million endowment from Amazon.com.
Guestrin provided an overview of the GraphLab distributed computation framework that’s being used to explore the capability of smaller computing systems to analyze enormous datasets.
One of the most dramatic examples Guestrin offered of its efficiency is a related project called GraphChi, which can use a Mac Mini PC to tally billions of Twitter relationships, doing in 18 seconds what previously took hours of work by a cluster of hundreds of computers.