The inaugural edition of PanamaHackea, an educational hackathon for the peoples of Panama, will be held on Saturday, September 29, 2018, in Torre de Las Américas, Panama City.  This event is the brainchild of 6 students from 4 schools, including Berkeley CS junior Rafael Félix, who hope to inspire and empower "a new generation of Panamanian designers, entrepreneurs, and engineers" by making new technologies more available and accessible to everyone.  In the months leading up to the event, they will create and share tutorials, workshops, tools and resources covering topics from the basics of programming to the latest in Machine Learning.  Participants will enjoy space, food, comaraderie, challenges, and prizes, in a supportive and collaborative environment.

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.

CS Ph.D. student Maxim Rabinovich (joint advisors: Michael Jordan and Daniel Klein) has received a 2018 Fannie and John Hertz Foundation Hertz-Gates Fellowship in Global Health and Development.  Rabinovich is currently researching machine learning and natural language processing, and is interested in developing artificial intelligence tools that support and extend human reasoning. Recent work in this direction includes projects on minimax theory for multiple testing, code generation from natural language specifications, fine-grained entity typing, and function-specific mixing rates for MCMC.  Rabinovich's work has been supported by the Hertz Foundation since 2015.

CS PhD student Chelsea Finn (advisers: Pieter Abbeel and Sergey Levine) has been named to MIT Technology Review's 2018 list of "35 Innovators Under 35," an honor which recognizes "exceptionally talented young innovators whose work we believe has the greatest potential to transform the world."  Finn is cited in the Pioneers category because "her robots act like toddlers—watching adults, copying them in order to learn."  She works in the Berkeley AI Research Lab (BAIR) developing robots that can learn just by observing and exploring their environment. Her algorithms require much less data than is usually needed to train an AI—so little that robots running her software can learn how to manipulate an object just by watching one video of a human doing it. “In many ways, the capabilities of robotic systems are still in their infancy,” she says. “The goal is to have them gain common sense.”

EECS undergraduate Tiffany Perumpail has won a Teaching Effectiveness Award (TEA) from the UC Berkeley Graduate Division.  This very competitive award is bestowed annually by the Graduate Council’s Faculty Advisory Committee for GSI Affairs.  Applicants submit essays in which they identify a problem they encountered in teaching, explain their strategy and rationale in devising a solution, and assess the effectiveness of the solution. Perumpail's essay, about her experience TAing CS61A, is titled "Improvement of Academic Intern Experience and Performance in Introductory Computer Science."  

Grad student Michael Chen (advisor:  Laura Waller) has been awarded a 2018 Optics and Photonics Education Scholarship by SPIE, the international society for optics and photonics, for his potential contributions to the field of optics, photonics or related field.  Chen works in the Computational Imaging Lab where he focuses on non-invasive multi-dimensional phase imaging. “Nowadays, computation enables us to truly utilize full capacity of existing imaging system and extract new information from decade-old optical designs. By jointly designing the optical hardware and post processing software, we deliver simple yet powerful computational imaging techniques,” he said.

"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.

Semantic Machines, an artificial intelligence startup co-founded by Prof. Dan Klein and staffed by a number of EECS alumni, has been acquired by Microsoft to help Cortana hold more natural dialog with users.  The team has built a number of machine learning components which work together for a smarter AI, and move beyond the more basic back-and-forth currently supported by the Google Assistant, Apple’s Siri, and Amazon’s Alexa.

In addition to Klein, the team includes Percy Liang (Ph.D. '11), David Hall (Ph.D. '12), Adam Pauls (Ph.D. '12), David Burkett (Ph.D. '12), Jason Wolfe (Ph.D. '11 adviser: Stuart Russell), Yuchen Zhang (Ph.D. '16), Taylor Berg-Kirkpatrick (B.A. '08/Ph.D. '15), Greg Durrett (Ph.D. '16), Alex Nisnevich (M.S. '14), current grad student Jacob Andreas, Charles Chen (B.A. CS/Math '11), Andrew Nguyen (B.A. CS/Linguistics '12), Chuck Wooters (Ph.D. Speech Recognition '93), and consultant Prof. Michael Jordan.

Assistant Prof. Rikky Muller and her Masters of Engineering students Jingbo Wu, Sherwin Lau, Paul Meyer-Rachner, Chen Fu and Mary Lee Lawrence, have received the 2018 Fung Institute Award for the Most Innovative Project.  This award is given to the team that most effectively demonstrates the relevance of the problem they are trying to solve, the originality of their proposed solution, and the potential of their project's impact. Their research project, "Neurodetect: On-Chip Biosignal Computation for Health Monitoring," was selected from over 100 capstone projects in the College of Engineering.  

Graduating CS senior Luke Strgar thinks he might have a solution for the fraught issue of guns in America: Use blockchain to track gun sales.  Strgar thinks that Blockchain offers the perfect balance between security, anonymity and scale that could please people on all sides of the gun-control debate.  He spent two days in Washington, D.C. this month pitching the idea of a centralized, ultra-secure, online gun-sale database to legislative aides and think-tank analysts.  A database like this could be monitored by everyone and could not be abused by the government.  “The goal here is to find a solution that both parties can agree on,” Strgar said. “I am not interested in developing something for one side of the discussion, that people try to force down the throat of parties coming from the other side. One of the nice things about technology is that you can develop systems that work for people.”