9 papers co-authored by 6 EECS faculty, 13 students,  3 post docs, and 3 alumni have made it into the Top 10 research papers ranked by TOPBOTS in four categories of AI Research. TOPBOTS is the largest publication, community, and educational resource for business leaders applying AI to their enterprises.  3 papers co-authored by Sergey Levine made the #1, #3, and #9 spots in "What Are Major Reinforcement Learning Achievements & Papers From 2018?"  A paper co-authored by Moritz Hardt ranked #5 in "Top 2018 AI research papers" and #3 in  "Recent Breakthrough Research Papers In AI Ethics." A paper co-authored by Jitendra Malik ranked #7 in the Top 2018 papers and #5 in "10 Cutting Edge Research Papers In Computer Vision & Image Generation."  The #2 Top 2018 paper was co-authored by David Wagner, and a paper co-authored by Alexei Efros ranked #9 in the Computer Vision category.

"Computer Architecture: A Quantitative Approach," 6th ed. by Prof. Emeritus David Patterson and John Hennessy has won a 2019 Textbook Excellence Award ("Texty") from the Text and Academic Authors Association (TAA).  Textys recognize excellence in current textbooks and learning materials. Works are judged by other textbook authors and subject matter experts who evaluate pedagogy, content/scholarship, writing, and appearance/design.  Patterson won a Most Promising New Textbook Award in 2016 for "Engineering Software as a Service: An Agile Approach Using Cloud Computing," 1st ed. co-authored by Prof. Armando Fox, and a McGuffey Longevity Award in 2014 for "Computer Organization and Design," 
5th ed. (also with Hennessy).

UC Berkeley computer theorists led by CS Prof. Umesh Vazirani,  published a proof of random circuit sampling (RCS) as a verification method to prove quantum supremacy in a paper published Monday, Oct. 29, in the journal Nature Physics.  Quantum supremacy is the term that describes a quantum computer’s ability to solve a computational task that would be prohibitively difficult for any classical algorithm.  “Besides being a milestone on the way to useful quantum computers, quantum supremacy is a new kind of physics experiment to test quantum mechanics in a new regime. The basic question that must be answered for any such experiment is how confident can we be that the observed behavior is truly quantum and could not have been replicated by classical means. That is what our results address,” said Vazirani.

A paper written by CS Prof. David Culler and alumnus Jonathan Hui (M.S. '05/Ph.D. '08) in 2008 titled "IP is Dead, Long Live IP for Wireless Sensor Networks" has won the Association of Computing Machinery (ACM) Conference on Embedded Networked Sensor Systems (SenSys) 2018 Test of Time Award.  The paper dispelled the notion that IP cannot run on wireless embedded sensors and made a long term impact  on standards like 6LoWPAN and platforms like Thread.  The award recognizes papers that are at least 10 years old and have had long lasting impact on networked embedded sensing system science and engineering.  Culler previously won this award in both 2014 and 2015.

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.

"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.