Professor Umans Receives Northrop Grumman Prize for Excellence in Teaching
Christopher Umans, Professor of Computer Science, is the recipient of the 2017 Northrop Grumman Prize for Excellence in Teaching. The Prize is awarded to an EAS professor who demonstrates, in the broadest sense, unusual ability, creativity, and innovation in undergraduate and graduate classroom or laboratory teaching. A nomination for Professor Umans read, “his course on computational complexity has become the de facto way that students decide if they're interested in computer science. It is an extremely challenging, mathematical course but his crisp, entertaining lectures bring everyone along.” Students in his class described it as, “my favorite class at Caltech so far", and ”I didn't think I liked theoretical CS until I took this course.”
The Mechanical Universe Now on YouTube
The critically acclaimed television series The Mechanical Universe… And Beyond, created at Caltech and broadcast on PBS from 1985-86, is now available in its entirety on YouTube thanks to the efforts of Caltech's Institute's Information Science and Technology initiative. [Caltech story] [Watch the show]
Alumnus Receives 2012 Simons Graduate Fellowships in Theoretical Computer Science
Christopher Beck (BS '09 Computer Science and Mathematics) is a recipient of a 2012 Simons Graduate Fellowship. The fellowships are given to graduate students in theoretical computer science with outstanding track records of research accomplishments. Beck’s work seeks to establish the limits of how efficiently we can solve computational problems. One of his papers studies a popular class of algorithms known as SAT solvers and shows that if their memory is restricted, then they can require exponential running time. Another result concerns how well we can approximately sample from certain distributions when our computation must be small depth, that is, highly parallelizable. Beck and his co-authors showed that even exponentially large bounded depth circuits cannot sample with even exponentially small success from a certain simple distribution.