News

Yang "Linda" Huang launches new novel: My Good Son

EECS Instructional Support Group (ISG) systems administrator Yang "Linda" Huang, has just published her third book, My Good Son (University of New Orleans Press, May 2021).  The novel, described as "layered, evocative and engaging" by Ms Magazine, had been selected for the University of New Orleans (UNO) Publishing Lab Prize "for the best unpublished novel or short story collection" by authors from around the world.  Like Huang's previous work, "My Good Son" focuses on the generational and cultural complexities of post-Tiananmen Chinese family life.  The story centers on a traditional Chinese father striving for the success of his son, and explores "the parallels and differences of American and Chinese cultures―father-son relationships, familial expectations, sexuality, social mobility, and privilege."  "My Good Son" was reviewed by both the  New York Times and the San Francisco Chronicle.  Huang, who was featured in the Chinese Literature Podcast on June 4th, will be participating in a Virtual Launch at Booksmith on June 9th, where she will engage in a conversation with author Kaitlin Solimine.

Tiny wireless implant detects oxygen deep within the body

CS Prof. and Chan Zuckerberg Biohub investigator Michel Maharbiz is the senior author of a paper in Nature Biotechnology titled "Monitoring deep-tissue oxygenation with a millimeter-scale ultrasonic implant," which describes a tiny wireless implant that can provide real-time measurements of tissue oxygen levels deep underneath the skin. The device, which is smaller than the average ladybug and powered by ultrasound waves, could help doctors monitor the health of transplanted organs or tissue and provide an early warning of potential transplant failure.  “It’s very difficult to measure things deep inside the body,” said Maharbiz. “The device demonstrates how, using ultrasound technology coupled with very clever integrated circuit design, you can create sophisticated implants that go very deep into tissue to take data from organs.”

New wearable device detects intended hand gestures before they're made

A team of researchers, including EECS graduate students Ali Moin, Andy Zhou, Alisha Menon, George Alexandrov, Jonathan Ting and Yasser Khan, Profs. Ana Arias and Jan Rabaey, postdocs Abbas Rahimi and Natasha Yamamoto, visiting scholar Simone Benatti, and BWRC research engineer Fred Burghardt, have created a new flexible armband that combines wearable biosensors with artificial intelligence software to help recognize what hand gesture a person intends to make based on electrical signal patterns in the forearm.  The device, which was described in a paper published in Nature Electronics in December, can read the electrical signals at 64 different points on the forearm.  These signals are then fed into an electrical chip, which is programmed with an AI algorithm capable of associating these signal patterns in the forearm with 21 specific hand gestures, including a thumbs-up, a fist, a flat hand, holding up individual fingers and counting numbers. The device paves the way for better prosthetic control and seamless interaction with electronic devices.

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.