News

Deep learning helps robots grasp and move objects with ease

CS Prof. Ken Goldberg is the co-author of a study published in Science Robotics which describes the creation of a new artificial intelligence software that gives robots the speed and skill to grasp and smoothly move objects, making it feasible for them to soon assist humans in warehouse environments.  He and postdoc Jeffrey Ichnowski had previously created a Grasp-Optimized Motion Planner that could compute both how a robot should pick up an object and how it should move to transfer the object from one location to another, but the motions it generated were jerky.  Then they, along with EECS graduate student Yahav Avigal and undergraduate (3rd year MS) student Vishal Satish, integrated a deep learning neural network into the motion planner, cutting the average computation time from 29 seconds to 80 milliseconds, or less than one-tenth of a second.  Goldberg predicts that, with this and other advances in robotic technology, robots could be assisting in warehouse environments in the next few years.

Jake Tibbetts wins Bulletin of the Atomic Scientists’ 2020 Leonard M. Rieser Award

EECS grad student and alumnus Jake Tibbetts (B.S. EECS/Global Studies '20) has won the Bulletin of the Atomic Scientists’ 2020 Leonard M. Rieser Award.   Winners of the award have published essays in the Bulletin's Voices of Tomorrow column, and are selected by the Bulletin’s editorial team for recognition as "outstanding emerging science and security experts passionate about advancing peace and security in our time."  Tibbetts received the award for his article “Keeping classified information secret in a world of quantum computing,” published in the Bulletin on February 11, 2020.  “In his piece, Jake Tibbetts accomplished the kind of deep, thoughtful, and well-crafted journalism that is the Bulletin's hallmark," said editor-in-chief John Mecklin. "Quantum computing is a complex field; many articles about it are full of strange exaggerations and tangled prose. Tibbetts' piece, on the other hand, is an exemplar of clarity and precision and genuinely worthy of the Rieser Award.”  Tibbetts is a fellow at the NNSA-supported Nuclear Science and Security Consortium, and has previously worked as a research assistant at the LBNL Center for Global Security Research.  He has made contributions to the Nuclear Policy Working Group and the Project on Nuclear Gaming at Cal, and made the EECS news last year for his involvement in creating the online three-player experimental wargame "SIGNAL," which was named the Best Student Game of 2019 by the Serious Games Showcase and Challenge (SGS&C).  The Rieser Award comes with a $1K prize.

"Extreme MRI" chosen as ISMRM Reproducible Research pick

"Extreme MRI: Large‐scale volumetric dynamic imaging from continuous non‐gated acquisitions,” a paper by EECS alumnus Frank Ong (B.S. '13, Ph.D. '18) and his advisor, Prof. Miki Lustig, has been chosen as October's Reproducible Research pick by the International Society for Magnetic Resonance in Medicine (ISMRM).  The paper, in which the researchers attempt to reconstruct a large-scale dynamic image dataset while pushing reconstruction resolution to the limit, was chosen "because, in addition to sharing their code, the authors also shared a demo of their work in a Google Colab notebook."  Lustig and Ong, now a research engineer at Stanford, participated in a Q&A in which they discussed how they became interested in MRI, what makes Extreme MRI "extreme," the culture and value of open science, and why Lustig's grad school paper on compressed sensing became the most cited paper in MRM.  ISMRM is an international nonprofit association that promotes research development in the field of magnetic resonance in medicine to help facilitate continuing education in the field.

Cecilia Aragon: Flying Free

CS alumna Cecilia Aragon (Ph.D. '04, advisors: Shankar Sastry and Marti Hearst) has written a memoir titled "Flying Free," which describes how she shook off the tethers of discrimination and her debilitating fear of heights to become the first Latina pilot to win a spot on the United States Unlimited Aerobatic Team, which represented the U.S. at the World Aerobatic Championships in 1991.  The daughter of a Chilean father and Filipina mother, Aragon earned her B.S. in Mathematics at Caltech before coming to Berkeley.  She was president of the student organization Women in Computer Science and Engineering (WICSE) in 1985 before dropping out.  After conquering her fears, she returned to Berkeley to complete her dissertation, "Improving Aviation Safety with Information Visualization:  Airflow Hazard Display for Helicopter Pilots," in 2004.  Aragon then spent nine years at the NASA Ames Research Center designing software for projects that included missions to Mars, before leaving to be a staff scientist/visiting faculty at LBNL for another 15 years. She then became the first Latina full professor at the University of Washington (UW), where has worked for the past ten years in the Department of Human Centered Design and Engineering, founding and co-directing the UW Data Science Masters Degree program.  Aragon was named Berkeley Computer Science Distinguished Alumna in 2013.  She co-authored a previous book, "Writers in the Secret Garden:  Fanfiction, Youth, and New Forms of Mentoring," released by MIT Press in 2019.

Paper by Peter Mattis to be presented at ACM SIGMOD conference

A paper co-written by EECS alumnus Peter Mattis (B.S. '97) is being presented at the 2020 Association for Computing Machinery (ACM) Special Interest Group on Management of Data (SIGMOD) International Conference on Management of Data this month.  The paper, titled "CockroachDB: The Resilient Geo-Distributed SQL Database," describes a cloud-native, distributed SQL database called CockroachDB, that is designed to store copies of data in multiple locations in order to deliver speedy access.  The database is being developed at Cockroach Labs, a company co-founded in 2015 by a team of former Google employees that included Mattis, who is also the current CTO, and fellow-alumnus Spencer Kimball (CS B.A. '97), currently the company CEO.  Cockroach Labs employs a number of Cal alumni including Ceilia La (CS B.A. '00) and Yahor Yuzefovich (CS B.A. '18).

11 EECS faculty among the top 100 most cited CS scholars in 2020

The EECS department has eleven faculty members who rank among the top 100 most cited computer science & electronics scholars in the world. UC Berkeley ranked #4  in the global list of universities with the highest number of influential scholars in 2020 (35, up from 24 in 2018).  Profs. Michael Jordan, Scott Shenker, Ion Stoica, Jitendra Malik, Trevor Darrell, David Culler, Shankar Sastry, Randy Katz, Alberto Sangiovanni-Vincentelli, Lotfi Zadeh and Dawn Song all ranked in the top 100 with an H-index score of 110 or higher, a measure that reflects the number of influential documents they have authored.   Jordan ranks fourth in the world, with an H-index of 166 and 177,961 citations.  The H-index is computed as the number h of papers receiving at least h citations among the top 6000 scientist profiles in the Google Scholars database. 

Michael McCoyd uses polio history to shed light on Coronavirus vaccine in NY Times Op-Ed

CS graduate student Michael McCoyd (advisor: David Wagner) has co-authored an op-ed piece in the New York Times titled "What to Expect When a Coronavirus Vaccine Finally Arrives," which offers sobering lessons from the history of the polio vaccine. It took over 60 years from the onset of the first polio epidemic for a safe and effective vaccine to be developed and attempts to hasten the process often led to tragedy. McCoyd, who is in the Secure Computing group, says the article arose from a class he took in the J-school to learn more about fighting disinformation titled "Science Denial: Role of the Media."  When the J-school shifted focus to COVID-19 coverage, Prof. Elena Conis, an historian of vaccination, suggested story ideas for the students to pitch.  With their pitch accepted by the New York Times, McCoyd and classmate Jessie Moravek, a graduate student in environmental science, wrote what became the op-ed with Prof. Conis.

Four papers authored by EECS faculty win Test-of-Time Awards at 2020 IEEE-SP

Four papers co-authored by EECS faculty (3 of which were co-authored by Prof. Dawn Song) have won Test-of-Time awards at the IEEE Symposium on Security and Privacy today: "Efficient Authentication and Signing of Multicast Streams Over Lossy Channels," co-authored by Song (Ph.D. '02) and the late Prof. Doug Tygar (with Perrig and Canetti) in 2000, "Practical Techniques for Searches on Encrypted Data," co-authored by Song and Prof. David Wagner (with Perrig) in 2000, "Random Key Predistribution Schemes for Sensor Networks," co-authored by Song (with Chan and Perrig) in 2003, and "Outside the Closed World: On Using Machine Learning For Network Intrusion Detection" co-authored by Prof. Vern Paxson (with Sommer) in 2010.    IEEE-SP is considered the premier computer security conference and this four-fold achievement demonstrates Berkeley's preeminence in the field.

Daniel Fremont wins ACM SIGBED Dissertation Award

Freshly-graduate CS Ph.D. student Daniel J. Fremont (advisor: Sanjit Seshia) has won the Association for Computing Machinery (ACM) Special Interest Group on Embedded Systems (SIGBED) Paul Caspi Memorial Dissertation Award for his thesis on "Algorithmic Improvisation."  The award, which was established in 2013, recognizes outstanding doctoral dissertations that significantly advance the state of the art in the science of embedded systems.  Fremont's thesis proposes a theory of algorithmic improvisation to enable the correct-by-construction synthesis of randomized systems, and explores its applications to safe autonomy.

Enabling robots to learn from past experiences

EECS Prof. Pieter Abbeel and Assistant Prof. Sergey Levine are developing algorithms that enable robots to learn from past experiences — and even from other robots.  They use deep reinforcement learning to bring robots past a crucial threshold in demonstrating human-like intelligence: the ability to independently solve problems and master new tasks in a quicker, more efficient manner.  An article in the Berkeley Engineer delves into the innovations and advances that allow Abbeel and Levine help robots make "good" choices, generalize between tasks, improvise with objects, multi-task, and manage unexpected challenges in the world around them.