News

Campus Shutdown Notice

In light of the ongoing coronavirus (COVID-19) situation, we have decided to close our administrative offices starting Monday, March 16, 2020 until further notice.  Cory and Soda Hall are closed.  Classes are being held remotely.  All events in Cory and Soda Halls will either be cancelled or held remotely, and staff will be working remotely during this time.

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.

Steven Cao and Stephen Tian

Steven Cao wins CRA 2021 Outstanding Undergraduate Researcher Award

Senior EECS student Steven Cao has won a Computing Research Association (CRA) 2021 Outstanding Undergraduate Researcher Award, and senior Stephen Tian was named runner-up.    The award recognizes significant contributions to computing research projects.  Cao (nominated by Prof. Dan Klein)  worked with the Berkeley Natural Language Processing group, where he developed new methods in syntactic parsing for one project, and contributed to the development and testing of new methods to provide more accurate translations between languages in another.  He also worked on developing new and provably correct blockchain protocols and on several projects related to medical imaging.  He co-authored seven papers, including first authorship on papers at three conferences.  He served as Teaching Assistant for two courses while also acting as a research mentor for the group.  Tian (nominated by Prof. Sergey Levine) demonstrated how a robotic finger with a touch sensor could perform myriad tasks using the same reinforcement learning algorithm in one project, and proposed a novel algorithm to allow a robot to achieve a variety of goals indicated as goal images in another.  He co-authored several papers at at least three conferences,  and served as a TA, while also volunteering at events for local high school students.   Ryan Lehmkuhl  (nominated by Prof. Raluca Ada Popa)a was a finalist, and Joey Hejna (nominated by Prof. Pieter Abbeel) received an honorable mention.

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.

Progress update: E3S 2019 Transfer-to Excellence program

The Center for Energy Efficient Electronics Science (E3S) Transfer-to-Excellence (TTE) research program is a competitive merit-based program that offers California community college students research opportunities at Berkeley in an effort to encourage them to transfer to a university to purse a Bachelor's degree in science and engineering.  A review of the current activities of the 2019 TTE cohort, whose members received ongoing mentorship over the past year through the TTE online mentoring program, shows that all of the interns are enrolled in science or engineering academic programs and working towards a Bachelor’s degree.  Among them:

Jared Brown (TTE project advisor: EECS Prof. Sayeef Salahuddin), who transferred from Los Angeles Pierce College to UCLA to study mechanical engineering, and is active in the UCLA Samueli Center for Excellence in Engineering and Diversity; Jose Camacho (advisor: EECS Prof. Ming Wu), who transferred from Los Angeles Trade Technical College to  UC San Diego to study Electrical Engineering; Saifuddin Mohammed (advisor: EECS Chair Jeff Bokor), who transferred from Foothill College to UC Berkeley to study EECS after having received the award for best engineering poster presentation at the 2019 SACNAS Diversity in STEM conference, and completing a research internship at LBNL;  current EECS undergrad Harutyun Rehanyan (advisor: ME Prof. Shawn Shadden), who transferred to Berkeley from Los Angeles Valley College after completing a research internship at Cal State Northridge, a software engineering internship with NASA JPL, and summer research at CMU’s Institute for Software Research; and current EECS undergrad Dao Dai (David) Tran (advisor: ME Prof. Shawn Shadden), who transferred from Orange Coast College to Berkeley after completing a software engineering internship at NASA JPL and a research internship at the University of Maryland in machine learning and artificial intelligence.

Gabe Fierro wins inaugural Google - CMD-IT FLIP Dissertation Fellowship

EECS graduate student Gabriel Fierro (B.S. c. 2014, Ph.D. advisor: David Culler) has won an inaugural Google - CMD-IT FLIP Dissertation Fellowship.   He is one of 11 computer science scholars from underrepresented groups who were recognized this year for "positively influencing the direction and perspective of technology."   The award is part of a joint effort by Google Research, the Computing Alliance of Hispanic-Serving Institutions (CAHSI), and the Center for Minorities and People with Disabilities in Information Technology (CMD-IT) Diversifying Future Leadership in the Professoriate (FLIP) Alliance to increase the diversity of doctoral graduates in computing.  After completing his Ph.D., Fierro aspires to "a faculty position in a computer science department where I am able to pursue non-traditional and cross-disciplinary approaches to long-standing problems of sustainability and the built environment."  Fierro is currently working on the Buildings, Energy and Transportation Systems project in conjunction with the RISE Lab.

Tiffany Chien and Jason Zhou named 2021 Siebel Scholars

EECS 5th Yr Masters students Tiffany Chien and Jason Zhou have been selected for the Siebel Scholars Foundation class of 2021.   They are among 92 distinguished engineering students from the "world’s leading graduate schools of business, computer science, bioengineering, and energy science" to win Siebel Scholars awards this year,  including eight from UC Berkeley.  Siebel Scholars are chosen for their "outstanding academic achievement and demonstrated leadership."  Chien is building a flexible simulation framework for calcium neuron imaging, simulating the 3D physical sample and the lens-less imaging system, and Zhou is interested in swarm intelligence, deep learning and robotics; his research has applications toward defense and disaster relief.

Victor Han selected runner-up for ISMRM I.I. Rabi Award

Third year EECS PhD candidate Victor Han (advisor: Prof. Chunlei Liu) was selected as a finalist for the International Society of Magnetic Resonance in Medicine (ISMRM) I.I. Rabi Young Investigator Award for original basic research.  He was chosen for his paper entitled “Multiphoton Magnetic Resonance Imaging,” in which he developed a novel technique that excites multiphoton resonances to generate signal for MRI by using multiple magnetic field frequencies, none of which is near the Larmor frequency. Only the total energy absorbed by a spin must correspond to the Larmor frequency. In contrast, today’s MRI exclusively relies on single-photon excitation. He was named runner-up at the ISMRM annual conference in early August.  Han will continue to develop his multiphoton technique and is exploring its applications in medicine and neuroscience as a part of his PhD dissertation research.  The ISMRM is a multi-disciplinary nonprofit professional association that promotes innovation, development, and application of magnetic resonance techniques in medicine and biology throughout the world. 

Rising Stars 2020, Berkley EECS, November 9-10, 2020

EECS to host Rising Stars 2020

UC Berkeley has been selected to host the Rising Stars 2020 Academic Career Workshop for Women in EECS, which will be held virtually on November 9-10, 2020.  Born at MIT in 2013 and last hosted by Berkeley in 2014, Rising Stars is an intensive workshop for women graduate students and postdocs who are interested in pursuing academic careers in computer science, computer engineering, and electrical engineering.  It will bring together senior-level PhD students, postdocs, faculty and special guests and  for a two-day intensive virtual workshop on the faculty search process.  Female-identifying EE and CS PhD graduate students who are within ~1-2 years of graduating, as well as postdocs who have obtained a PhD no earlier than 2017, are encouraged to apply.  The application deadline is deadline is September 7, 2020.

Ava Tan wins DRC 2020 Best Paper Award

EECS graduate student Ava Jiang Tan (advisor: Sayeef Salahuddin) has won the 2020 Best Paper Award at the 78th Device Research Conference (DRC) for "Reliability of Ferroelectric HfO2-based Memories: From MOS Capacitor to FeFET."  The paper, co-authored by Profs. Salahuddin and Chenming Hu, grad student Yu-Hung Liao, postdoc Jong-Ho Bae, and Li-Chen Wang of MSE, introduces nonvolatile ferroelectric field-effect transistors (FeFETs) which boast impressive programmability and a strong potential for further scalability.  The paper also demonstrates for the first time a systematic, reliable, and rapid method to qualitatively predict the FE endurance of prospective gate stack designs prior to running a full FeFET fabrication process.  Tan works in the Laboratory for Emerging and Exploratory Devices (LEED), and is particularly interested in the architectural potential of nonvolatile ferroelectric CMOS-compatible memories for realizing brain-inspired computing paradigms and energy-efficient hardware for deep learning. The DRC, which is the longest-running device research meeting in the world,  was held in June.