CS Prof. Hany Farid is launching a major survey of people in the United States and Western Europe to determine how far COVID-19 misinformation has penetrated the population. Using Amazon’s Mechanical Turk survey software, he and his research team hope to interview thousands of people in an effort to better understand how misinformation is being distributed, consumed, and spread.  Farid will work with other researchers and social media platforms to develop strategies on how to stop misinformation before it can take hold.

EECS Associate Profs. Prabal Dutta and Robert Pilawa-Podgurski have embarked on a project with doctors at UCSF to develop cost-effective powered air-purified respirators (PAPR) that will offer greater protection for healthcare workers from the coronavirus during higher risk medical procedures.  They are using an approach originally proposed to them by Oakland resident Lakin Moser, to explore a do-it-yourself PAPR concept that would be medically acceptable, inexpensive to build and rapidly scalable for regional, national and global needs.  Their prototype, which is made with a combination of off-the-shelf components and custom electronic circuits and mechanical parts sourced from Bay Area manufacturers and major electronics distributors, will cost $200 per unit--ten times less than standard devices--and can be manufactured at scale in weeks. “A key aspect of the design was to source components that are widely available, and to provide modularity to enable swap-in of alternatives if supply chain issues arise,” said Pilawa-Podgurski.  The latest version of their prototype, which was built in the team's garages and basements,  is currently undergoing usability testing at UCSF Medical Center to ensure that it meets clinical standards.  The team plans to post their design on the web as soon as it is finalized for production.

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.

EECS Prof. and alumna Dawn Song (Ph.D. '02, advisor: Doug Tygar) and Assistant Prof. Raluca Ada Popa are featured in the cover story for the Spring 2020 issue of the Berkeley Engineer titled "Reinventing Cybersecurity."  Faced with the challenge of protecting users' personal data while recognizing that sharing access to that data "has fueled the modern-day economy" and supports scientific research, Song has proposed a paradigm that involves "controlled use" and an open source approach utilizing a new set of principles based on game theory.  Her lab is creating a platform that applies cryptographic techniques to both machine-learning models and hardware solutions, allowing users to keep their data safe while also making it accessible.  Popa's work focuses on using machine-learning algorithms to keep data encrypted in cloud computing environments instead of just surrounding the data with firewalls.  "Sharing without showing" allows sensitive data to be made available for collaboration without decryption.  This approach is made practical by the creation of a machine-learning training system that is exponentially faster than other approaches. "So instead of training a model in three months, it takes us under three hours.”

EECS Prof. Pieter Abbeel and Assistant Prof. Sergey Levine both appear in a New York Times article titled "Computers Already Learn From Us. But Can They Teach Themselves?" which describes the work of scientists who "are exploring approaches that would help machines develop their own sort of common sense."  Abbeel, who runs the Berkeley Robot Learning Lab, uses reinforcement-learning systems that compete against themselves to learn faster in a method called self-play.  Levine, who runs the Robotic AI & Learning Lab, is using a form of self-supervised learning in which robots explore their environment to build a base of knowledge.

EE Prof. in Residence Yi Ma has been selected to be a 2020 Fellow of the Society for Industrial and Applied Mathematics (SIAM).    SIAM Fellows are members of SIAM "who have made outstanding contributions to fields" served by the SIAM community.  Ma was recognized "for contributions to the theory and algorithms for low-dimensional models and their applications in computer vision and image processing."

CS major Jason (XiangJun) Li and a few friends have developed a website designed to provide clear, reliable, up-to-date numbers and trends on the COVID-19 outbreak "for average Americans," particularly those on mobile phones.  LiveCoronaUpdates.org, which was launched last Tuesday, uses data released by the World Health Organization and official government websites, and provides "the simplest and most intuitive dashboard for people to quickly understand the trends and assess risks."  The site includes domestic and global numbers of patients confirmed/recovered/dead, simple graphics and tables, a headline feed, and text alerts using data that is updated every 3 hours.

EE Prof. and alumnus Chenming Hu (M.S. '70, Ph.D. '73), who won the 2020 IEEE Medal of Honor, has chosen to donate his $50K prize to the EECS department.   Hu, who was cited “for a distinguished career of developing and putting into practice semiconductor models, particularly 3D device structures, that have helped keep Moore’s Law going over many decades," is also the subject of an IEEE Spectrum article.  He was hired on the Berkeley faculty in 1976 and has been called the "Father of the 3D Transistor" due to his development of the Fin Field Effect Transistor in 1999.  Intel, the first company to implement FinFETs in its products, called the invention the most radical shift in semiconductor technology in more than 50 years.

The 4th Annual Women In Tech Symposium, part of the Women In Tech Initiative (WITI) will be held at UC Berkeley on Friday, March 6, 2020.  The theme will be "Reimagining Cybersecurity for All."  Many members of the EECS community will be involved, including: alumna and Prof. Dawn Song (PhD '02) - opening remarks; WITI@UC co-founder and dean of Engineering Prof. Tsu-Jae King Liu - fireside chat; Prof. Raluca Ada Popa - Panel: What’s at Stake? Global and Systemic Cyber Threats;  and CITRIS Director Prof. Costas Spanos - Athena Awards presentation. Tickets will be available until Monday, March 2nd.

Research on Microrelays presented at the IEEE International Electron Devices Meeting (IEDM) by Prof. Tsu-Jae King Liu and alumna/graduate student, Xiaoer Hu (M.S. '18), is highlighted in an IEEE Spectrum article titled "4 Ways to Make Bigger Quantum Computers."  It is difficult to scale quantum computers because quantum-computer processors must operate inside cryogenic enclosures at near absolute zero, but the electronics needed for readout and control don’t work at such temperatures and must reside outside the refrigerator.  King Liu and Hu have developed micrometer-scale electromechanical relays as ultralow-power alternatives to transistors that operate better when cooled to 4 kelvins than at room temperature.  Freezing temperatures solve two of the mechanical problems the devices encounter:  the reaction of ambient oxygen on electrode surfaces, and the way that microscale relays tend to stick together.  “We didn’t suspect ahead of time that these devices would operate so well at cryogenic temperatures,” says King Liu. “In retrospect, we should have.”