Teaching Prof. Dan Garcia is featured in an EdSurge article titled "Engineers, Recruiters and Professors Weigh In: Future Programmers Need Writing Skills, Too," in which he discusses how career goals should shape a student's skill set.  Although not all successful coders need to be proficient writers, flexibility is important.  “There are careers where someone doesn't need [to write]… but we want students to be able to go to any position. Maybe they want to just be a coder [at first], but later they decide to be an academic or on the documentation side or in management,” says Garcia. “My point is you never know when you need to write.”

In a somewhat related Daily Cal article, undergrad Sanil Rajput ponders the correlation between copy editing and computer science, putting forth a theory that "Copy editors make excellent coders."

CS majors Jimmy Liu and Zuhayeer Musa are featured in a Berkeley News article titled "In undergrad startup class, students learn to build the future."  Liu and Musa co-founded a startup called Bash while still in high school.  When they came to Cal, they partnered with CS Prof. Scott Shenker to launch a student-run DeCal class on Berkeley's startup ecosystem last spring, called "How to Build the Future."  The course gives students direct experience with world-renowned entrepreneurs and faculty founders.

CS Prof. Pieter Abbeel, graduate student Chelsea Finn, and Brett the robot are featured in a Wired article titled "The Education of Brett the Robot" which delves into some of the nuts and bolts of machine learning.  Brett (short for Berkeley Robot for the Elimination of Tedious Tasks) is using a reinforcement learning algorithm to allow it to learn from its mistakes.  Abbeel will speak on "Deep Learning-to-Learn Robotic Control" at the EECS Colloquium on October 11th.

Senior CS major Saloni Shah and Teaching Prof. Dan Garcia are featured in a TechRepublic cover story titled "The state of women in computer science: An investigative report."   They discuss some of the challenges of attracting and retaining women students in computer science, and some of the efforts that Berkeley has made to bridge the gap.  Shah has interned at Google the past two summers and has participated in—and won—several collegiate hackathons.  She describes instances where her fellow students have suggested that her achievements were the result of affirmative action.  "I have all of these projects," she says. "I have definitely shown I can do it."  "I don't think they actually believe that women don't belong in computer science," she adds. But when they say that her accomplishments were possible only because she received special treatment as a woman, she explains that it's usually "a means of justifying why they didn't get something."

Management, Entrepreneurship, & Technology Program (M.E.T.) student Arvind Sridhar (CS/Business) has been awarded a $25,000 Davidson Fellows scholarship.  The award is presented annually by the Davidson Institute for Talent Development to 20 students based on “significant work” in science, technology, engineering, mathematics, literature, music and philosophy. Sridhar’s scholarship was granted based on a study he undertook at the Stanford University School of Medicine over the summer.  He sought to create algorithms and computational models that would allow doctors to diagnose the health of cardiac tissue using only images and videos of a tissue sample, and then use an injectable hydrogel, which mimics the heart’s micro-environment, to anchor and nourish stem cells to parts of the heart, allowing them to enable cardiac regeneration.

CS Ph.D. student Pulkit Agrawal (advisers: Jitendra Malik and Jack Gallant) is the subject of a Quant Magazine article titled "Clever Machines Learn How to Be Curious."  Agrawal is working at the Berkeley Artificial Intelligence Research Lab with CS grad student Deepak Pathak, Pathak's adviser Prof. Trevor Darrell, and CS Prof. Alexei A. Efros,  to design experimental machine-learning algorithms which aim to "make a machine curious."  They equipped their learning agent with what they call an intrinsic curiosity module (ICM) designed to pull it forward through a video game without going haywire, despite having no prior understanding of the game. “You can think of curiosity as a kind of reward which the agent generates internally on its own, so that it can go explore more about its world,” Agrawal said.

CS/IEOR Prof. Ken Goldberg, director of the AUTOLAB, and his EE graduate student Jeff Mahler, are profiled in a  New York Times article titled "In the Future, Warehouse Robots Will Learn on Their Own," about researchers who are using neural networks and machine learning to teach robots to grab things they have never encountered before.   The AUTOLAB robot was trained by being shown hundreds of purely digital objects, after which it could pick up items that weren’t represented in its digital data set.  “We’re learning from simulated models and then applying that to real work,” said Goldberg,

For the second year in a row, U.C. Berkeley has ranked No. 2 among the 50 undergraduate programs that produce the most venture capital-backed entrepreneurs, according to PitchBook’s 2017-18 report.  The report distinguishes undergraduate and MBA programs, compares Ivy League colleges to other universities and analyzes numbers such as companies per sector, female founders and total capital raised by founders’ companies. This year, UC Berkeley produced 1,089 entrepreneurs and 961 companies.

Graduate student Yang You (advisor: James Demmel) has won a 2017 ACM IEEE Computer Society George Michael Memorial Fellowship for his work on designing accurate, fast, and scalable machine learning algorithms on distributed systems.   The award, which was named in honor of George Michael, one of the founding fathers of the Supercomputing (SC) Conference series, is given in recognition of overall potential for research excellence in subjects of interest to the High Performance Computing (HPC) community.  In You's most recent work, “Scaling Deep Learning on GPU and Knights Landing Clusters,” his goal is to scale up the speed of training neural networks so that networks which are relatively slow to train can be redesigned for high performance clusters. This approach has reduced the percentage of communication from 87% to 14% and resulted in a five-fold increase in speed.

Enrollment in CS 61A, The Structure & Interpretation of Computer Programs,  has increased from 1,568 students last fall to 1,762 students this semester.  CS 61A is a popular introductory coding class--a requirement for EECS majors--co-taught by Assistant Teaching Professor Jon DeNero and Prof. Paul Hilfinger.  The live lecture attendance is expected to drop as students discover that lectures are being webcasted three different times for about 600 students each time.  “We have enough funding and enough TAs [over 50] and, as of yesterday, I think we have enough rooms,” DeNero said.  Additional student support is provided by discussion sections, expanded small group-mentoring sections, and pilot online versions of discussions and labs.  Last fall, 60 percent of the students rated their class experience 5/5.