The Foundations of Data Science (Data 8X), which is being offered free online this spring for the first time through the campus’s online education hub, edX, is the fastest-growing course in UC Berkeley’s history.  Taught by Prof. David Wagner,  Assistant Teaching Prof. John DeNero (recipient of the 2018 Distinguished Teaching Award), and a statistics professor, Data 8X is based on CS C8: Foundations of Data Science and now has more than 1,000 students enrolling every semester.  “You’ll learn to program when studying data science — but not for the primary purpose of building apps or games,” says DeNero. “Instead, we use programming to understand the world around us.”

The Association of Computing Machinery (ACM) announced today that the winners of the 2017 ACM Turing Award are UC Berkeley's David A. Patterson and Stanford University's John L. Hennessy for "pioneering a systematic, quantitative approach to the design and evaluation of computer architectures with enduring impact on the microprocessor industry. Hennessy and Patterson created a systematic and quantitative approach to designing faster, lower power, and reduced instruction set computer (RISC) microprocessors." (ACM) Since then, computer architects have been using principles derived from their approach in a wide variety of projects for industry and academia.  Today, 99% of the more than 16 billion microprocessors produced annually are RISC processors, to be found in most smartphones, tablets, and the billions of embedded devices that comprise the Internet of Things (IoT).  

The Berkeley Electrical Engineering and Computer Engineering programs have been ranked #1 and #2 respectively by U.S.News & World Report, continuing our tradition as one of the best EECS graduate programs the world.  In the 2019 rankings, Electrical/Electronic/Communications Engineering moved up from #3 to #1, tying with MIT and Stanford.  Computer Engineering held the #2 spot between MIT and UI Urbana-Champaign.  The College of Engineering graduate programs held the #3 spot under MIT and Stanford, with #1 rankings in Civil and Environmental/Environmental Health, a #2 ranking in Chemical Engineering, #3 rankings in Industrial/Manufacturing/Systems, Materials,and Mechanical, and a #4 ranking in Biomedical/Bioengineering.

EE postdoctoral fellow Amal El-Ghazaly, who works with the Nanoelectronics and Nanostructures Group, is featured in a Berkeley News article as one of the 25 scholars from Berkeley, Stanford, Caltech and UCLA who’ve won postdoctoral fellowships from the NSF-sponsored California Alliance for Graduate Education and the Professoriate (AGEP).  The alliance was formed to address the seemingly intractable ethnic underrepresentation in key STEM fields in the postdoctoral and faculty ranks at prestigious universities.  Aspiring professor El-Ghazaly, a hijab-wearing Muslim of African heritage, was often the only underrepresented minority student, and sometimes the only woman, in her specialized applied physics courses at CMU and Stanford.  The Berkeley-led Alliance will share its challenges and successes at the Pathways to a Diverse Professoriate conference on campus this week.

Assistant Teaching Prof. John DeNero has won the UC Berkeley Distinguished Teaching Award.   The award, presented by the Academic Senate, recognizes U.C. Berkeley's brightest teaching stars for their inspiring and transformational teaching.  DeNero says his teaching goal is not necessarily to make students happy but to help them learn how to solve problems that they thought they couldn't solve.  He has a knack for grabbing attention, exciting students, and in many ways, serving as a pioneer.  He teaches his introductory course for computer science majors, CS 61A, to nearly 1,600 students in 47 sections with the help of a course staff of 95 undergraduates. Distinguished Teaching Award winners are frequently called upon by the campus to provide a voice on issues related to teaching. They serve on forums, panels, and committees involving teaching issues, and they are advocates for excellence in teaching at Berkeley.

College of Engineering Distinguished Alumna Barbara Simons (Ph.D. '81) is the subject of an article in the Dail Kos titled "Computer scientist Barbara Simons proves how easy it is to hack elections—and how it can be stopped."  Simons,  who runs Verified Voting, has been a longtime advocate for bringing paper ballots back to all states and exposing the perils of electronic paperless ballots.  Last summer, she ran an experiment at the Def Con Hacker Conference in Las Vegas in which she secured 4 voting machines and had two teams of hackers successfully compromise them. “Anything that’s happening in here, you can be sure [it’s something] that those intent on undermining the integrity of our election systems have already done,” she said.  Simons will be a keynote speaker at the WiCSE 40th Reunion on Saturday.

Prof. Michael Jordan has been named a Plenary Lecturer at the 2018 International Congress of Mathematicians (ICM), which will take place in Rio de Janeiro, Brazil, in August.  ICM is considered the world’s premier forum for presenting and discussing new mathematical discoveries.  Plenary speakers are invited from around the world to present one-hour lectures which are held without other parallel activities--an honor that has been bestowed on only a small handful of computer scientists over the 121 year history of the ICM.

Undergraduate students Ganeshkumar Ashokavardhanan (EECS  + Business M.E.T.),  Naomi Jung (CS BA), and Louie McConnell (EECS + Business M.E.T.) have been selected to participate in the 2018 KPCB Engineering Fellows Program, named one of the top 5 internship programs by Vault.  Over the course of a summer, KPCB Engineering Fellows join portfolio companies, where they develop their technical skills and are each mentored by an executive within the company. It offers students an opportunity to gain significant work experience at Silicon Valley startups, collaborating on unique and challenging technical problems.

A paper released on arXiv last week by a team of researchers including Prof. Dawn Song and Ph.D. student Nicholas Carlini (B.A. CS/Math '13), reveals just how vulnerable deep learning is to information leakage.  The researchers labelled the problem “unintended memorization” and explained it happens if miscreants can access to the model’s code and apply a variety of search algorithms. That's not an unrealistic scenario considering the code for many models are available online, and it means that text messages, location histories, emails or medical data can be leaked.  The team doesn't “really know why neural networks memorize these secrets right now, ” Carlini says.  “At least in part, it is a direct response to the fact that we train neural networks by repeatedly showing them the same training inputs over and over and asking them to remember these facts."   The best way to avoid all problems is to never feed secrets as training data. But if it’s unavoidable then developers will have to apply differentially private learning mechanisms, to bolster security, Carlini concluded.