In an effort to gather scientists at the interface between neurosciences, optical engineering, and computer science, an all-day conference is being held on Friday, June 9, in Stanley Hall titled Sculpted Light in the Brain.   Participants are united in their mission to develop technologies to enable real time optical communication with the living brain.  The endeavor was initiated with a $2k seed grant to the California Institute for Quantitative Biosciences (QB3) and grew into a $20K showcase for the collaboration between neuroscientists, electrical engineers, and computer scientists, highlighting U.C. Berkeley's position as a preeminent leader in brain research. The conference, which already has a 50 person waitlist, will host 11 fully funded speakers including EE Associate Prof. Laura Waller,  present 25 posters, and is supported by a dozen corporate sponsors .

Many researchers are working on ways for robots to learn to grasp and manipulate things by practicing over and over, but the process is very time-consuming. The research work on robotic deep learning by Prof. Ken Goldberg is featured on the cover of MIT Review in an article titled "Meet the Most Nimble-Fingered Robot Yet".  Instead of practicing in the real world, Prof. Ken Goldberg and colleagues have developed a robot that learns by feeding on a data set of more than a thousand objects that includes their 3-D shape, visual appearance, and the physics of grasping them. This data set was used to train the robot’s deep-learning system. Advances in control algorithms and machine-learning approaches, together with new hardware, are steadily building a foundation on which a new generation of robots will operate.

Prof. David Culler has been appointed the Interim Dean for the newly created Division of Data Sciences.  The purpose of the new division is to bring techniques to bear in statistics, mathematics, and computer science on new sources of data.  One of their goals is the creation of an undergraduate data science major and data science minor.   Prof. Culler's duties will include fostering a cooperative atmosphere among the relevant faculties; working with the administration to form an advisory board with representation of key external constituencies; advancing fundraising efforts in concert with broader campus fundraising objectives; and enlisting a team of Berkeley faculty members who will work with him to develop the initiative. He will begin his new role on July 1, 2017 for a two-year term.

CS Prof. Stuart Russell gave an engaging TED talk in April describing some of the problems in, and possible solutions for, creating a species that is smarter than humans.  He argues that building provably altruistic,  humble, and humanitarian machines might help us avoid some of the pitfalls inevitable in a future with superintelligent AI.

Computer vision pioneer Prof. Avideh Zakhor is the subject of a Mercury News profile titled "Avideh Zakhor: the brains behind Google Earth and Street View,"  which touches on her emigration from Iran,  the creation of the 3-D city modeling technology for a Defense Department-funded start-up which she ultimately sold to Google, and her current research on indoor mapping.  She also discusses the value of encouraging skilled immigrant workers to come to the U.S and the importance of getting more women into STEM fields.  "Maybe then we wouldn’t in Silicon Valley have a shortage of STEM workers — it makes it very hard for tech companies to operate; the labor market is very tight." she says.

Prof. Richard Karp and coauthors Jacob Scott, Trey Ideker and Roded Sharan have received the 2017 RECOMB (International Conference on Research in Computational Molecular Biology) Test of Time Award for their paper "Efficient Algorithms for Detecting Signaling Pathways in Protein Interaction Networks". Prof. Karp also won awards at RECOMB 14 and RECOMB 16.

Prof. Emeritus David Patterson is profiled in a CNBC article which describes how he postponed retirement to conduct research at Google into the Tensor Processing Unit (TPU), an ambitious new chip that's designed to run at least 10 times faster than today's processors and is sophisticated enough to handle the intensive computations required for artificial intelligence.  Without it, it is estimated that Google would have to double its data centers to support even a limited amount of voice processing.  Prof. Patterson described his work on the TPU when he returned to Berkeley as a Colloquium speaker on May 3rd.

Assistant Prof. Rikky Muller has been awarded the 2017 Keysight Early Career Professor Award. The Keysight Early Career Professor Award is established to recognize and encourage excellent research enabling design, test or measurement of electronic systems. The program seeks to establish strong collaborative relationships between Keysight researchers and leading professors early in their careers and to highlight Keysight's role as a sponsor of university research. Prof. Muller's expertise is in the research and commercialization of implantable medical devices and in developing microelectronic and integrated systems for neurological applications. She is also the Co-founder of Cortera Neurotechnologies, Inc. a medical device company founded in 2013 that is commercializing a neural implant device and has released a family of products for the animal neuroscience research market. At Cortera, she held positions as CEO and CTO.

Professors Jan Rabaey and Pieter Abbeel were named in the top 5 of the 2017 top 50 pioneers by the “De Tijd” (translation buttons provided above the article), the Belgian equivalent of the Financial Times. Prof. Rabaey is currently the scientific co-director of the Berkeley Wireless Research Center (BWRC) as well as the director of the FCRP Multiscale Systems Research Center (MuSyC), and is involved with the Donald O. Pederson Center for Design Automation (DOP), SWARM Lab,  CITRIS People and Robots (CPAR), TerraSwarm Research Center, and the  Center for Neural Engineering & Prostheses (CNEP). His research interests include ultra-low energy wireless exploring the boundaries of ultra-low energy design and the design of microscopic systems, including all components from energy sources, conversion and storage, interfaces, digital and mixed signal. Prof. Abbeel is currently a member of the steering committee of the Berkeley Artificial Intelligence Research Center (BAIR) and is involved with the Center for Human Compatible Artificial Intelligence (CHCAI), Berkeley Vision and Learning Center (BVLC), Center for Automation and Learning for Medical Robotics (Cal-MR) and CITRIS People and Robots (CPAR). His current research area is primarily studying deep learning for robotics, where learning could be from demonstrations (apprenticeship learning) or through the robot's own trial and error (reinforcement learning). Targeted application domains include autonomous manipulation, flight, locomotion and driving.

Prof. Jitendra Malik has been named recipient of the Association for Computing Machinery (ACM) and Association for the Advancement of Artificial Intelligence (AAAI) Allen Newell Award. The Allen Newell award is presented to an individual for career contributions that have breadth within computer science, or that bridge computer science and other disciplines. Prof. Malik's research has addressed several important problems in computer vision: how to characterize contours in images, how to segment images, and how to represent shape for feature matching.  He also was a leader in evaluation methods through the creation of the Berkeley segmentation dataset, using human segmentations to evaluate the correctness of the algorithmic segmentations.  He pioneered the use of normalized cuts, anisotropic diffusion, high dynamic range imaging, shape context and the use of graph theory for low-level to mid-level computer vision problems.  In computer graphics, his research showed how digital photographs and user-guided photogrammetry can be used to synthesize highly photorealistic computer-generated architectural scenes.  He also has made important contributions to computational models of human texture perception including segmentation, shape from texture, and intrinsic image computation.