2005 CS Distinguished Alumna Barbara Simons (Ph.D. '81) is the subject of a Berkeley Engineering profile celebrating the 150th anniversary of U.C. Berkeley.  Simons, who is a past president of the Association for Computing Machinery (ACM), has been drawing attention to the pitfalls of electronic voting since 2003.  She's a vocal critic of electronic ballots and is board chair of Verified Voting, a non-partisan organization that advocates for reliable and secure voting practices, as well as the author of a book titled “Broken Ballots: Will Your Vote Count?”   She is also a long-time champion for programs to increase diversity in computer science and engineering.

UC Berkeley is the top ranked university in the third annual Octoverse Report list of "Open source contributions made by employees of different organizations," with 2700 contributions.  Berkeley is the fourth ranked organization overall--after Microsoft, Google, and Red Hat.  The Octoverse Report is a roundup of GitHub data across global repositories from the last 12 months.  Four other universities made the top ten:  the University of Washington  (6th place with 1800 contributions), MIT (8th place with 1700), UMich and Stanford (tied 9th with 1600 contributions each) .  

CS postdoctoral researcher Urmila Mahadev (advisor: Umesh Vazirani) has come up with an interactive protocol by which users with no quantum powers of their own can employ cryptography to put a harness on a quantum computer and drive it wherever they want, with the certainty that the quantum computer is following their orders.  Her work, which addressed the question "How do you know whether a quantum computer has done anything quantum at all?" was awarded the “best paper” and “best student paper” prizes when it was presented at the Symposium on Foundations of Computer Science this month.  CIT computer scientistThomas Vidick calls her result “one of the most outstanding ideas to have emerged at the interface of quantum computing and theoretical computer science in recent years.”

CS alumnus Jun-Yan Zhu (Ph.D. '17, advisor: Alexei Efros) has won the Association for Computing Machinery (ACM) Special Interest Group on Computer Graphics and Interactive Techniques (SIGGRAPH) Outstanding Doctoral Dissertation Award. Zhu is a pioneer in the use of modern machine learning in computer graphics. His dissertation is arguably the first to systematically attack the problem of natural image synthesis using deep neural networks. As such, his work has already had an enormous impact on the field, with several of his contributions, most notably CycleGAN, becoming widely-used tools not just for researchers in computer graphics and beyond, but also for visual artists.

EECS graduate students Nick Antipa and Grace Kuo, along their advisor Associate Prof. Laura Waller, have penned an article for Photonics Media titled "Lensless Cameras May Offer Detailed Imaging of Neural Circuitry" about a new architecture which could enable simultaneous monitoring of millions of neurons in 3D space at frame rates limited only by image sensor read times.  Instead of using a large, lens-based light-field microscope to image individual brain neurons, the DiffuserCam lensless imaging architecture consists of a diffuser placed in front of a 2D image sensor. When an object is placed in front of the diffuser, its volumetric information is encoded into a single 2D measurement.   Borrowing tools from the field of compressed sensing, a 3D image is reconstructed by solving a sparsity-constrained optimization problem.

"PerfFuzz: Automatically Generating Pathological Inputs," written by graduate students Caroline Lemieux and Rohan Padhye, and Profs. Koushik Sen and Dawn Song, will receive a Distinguished Paper Award from the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2018 in Amsterdam in July.  PerfFuzz is a method to automatically generate inputs for software programs via feedback-directed mutational fuzzing.  These inputs exercise pathological behavior across program locations, without any domain knowledge.   The authors found that PerfFuzz outperforms prior work by generating inputs that exercise the most-hit program branch 5x to 69x times more, and result in 1.9x to 24.7x longer total execution paths.

CS alumnus Aviad Rubinstein (Ph.D. ' 17, advisor: Christos Papadimitriou) is the recipient of the Association for Computing Machinery (ACM) 2017 Doctoral Dissertation Award for his dissertation “Hardness of Approximation Between P and NP.”  In his thesis, Rubinstein established the intractability of the approximate Nash equilibrium problem and several other important problems between P and NP-completeness—an enduring problem in theoretical computer science.  His work was featured in a Quanta Magazine article titled "In Game Theory, No Clear Path to Equilibrium" in July. After graduating, Rubinstein became a Rabin Postdoc at Harvard and will join Stanford as an Assistant Professor in the fall.

The research of Associate Prof. Laura Waller is highlighted in a Berkeley News article titled "Editing brain activity with holography."  Waller is co-author of a paper published in the journal Nature Neuroscience that describes a holographic brain modulator which can activate up to 50 neurons at once in a three-dimensional chunk of brain containing several thousand neurons, and repeat that up to 300 times a second with different sets of 50 neurons. The goal is to read neural activity constantly and decide, based on the activity, which sets of neurons to activate to simulate the pattern and rhythm of an actual brain response, so as to replace lost sensations after peripheral nerve damage, for example, or control a prosthetic limb. “The major advance is the ability to control neurons precisely in space and time,” said Waller's postdoc Nicolas Pégard, who is a first author of the paper.  “In other words, to shoot the very specific sets of neurons you want to activate and do it at the characteristic scale and the speed at which they normally work.”

Researchers, including Prof. Vladimir Stojanović, have developed a method to fabricate silicon chips that can communicate with light and are no more expensive than current chip technology.  Stojanovic initially led the project into a new microchip technology capable of optically transferring data which could solve a severe bottleneck in current devices by speeding data transfer and reducing energy consumption by orders of magnitude.  He and his collaborators, including Milos Popović at Boston University and Rajeev Ram at MIT, recently published a paper in Nature where they present a manufacturing solution by introducing a set of new material layers in the photonic processing portion of a bulk silicon chip. They demonstrate that this change allows optical communication with no impact on electronics.

CS Prof. Eric Paulos and his graduate students in the Hybrid Ecologies Lab, Sarah Sterman, Molly Nicholas, and Christine Dierk, have created a prototype of a wearable color- and shape-changing braid called HäirIÖ.  The hair extension is built from a custom circuit, an Arduino Nano, an Adafruit Bluetooth board, shape memory alloy, and thermochromic pigments.  The bluetooth chip allows devices such as phones and laptops to communicate with the hair, causing it to change shape and color, as well as respond when the hair is touched. Their paper "Human Hair as Interactive Material," was presented at the ACM International Conference on Tangible, Embedded and Embodied Interaction (TEI) last week. They have posted a how-to guide and instructable videos which include comprehensive hardware, software, and electronics documentation, as well as information about the design process. "Hair is a unique and little-explored material for new wearable technologies," the guide says.  "Its long history of cultural and individual expression make it a fruitful site for novel interactions."