Michael Jordan and the implications of algorithmic thinking

CS Prof. Michael I. Jordan is featured in This Week in Machine Learning & AI (TWIML AI) Podcast episode #407 titled "What are the Implications of Algorithmic Thinking? with Michael I. Jordan."   He discusses his current exploration into the intersection of economics and AI, and how machine learning systems could be used to create value and empowerment across many industries through “markets.”  The interview also touches on the potential of “interacting learning systems” at scale, the valuation of data, and the commoditization of human knowledge into computational systems.  Jordan's career, and the ways it has been influenced by other fields like philosophy, is also explored.  Jordan received the 2020 IEEE John von Neumann Medal for "outstanding achievements in computer-related science and technology" earlier this year.

Dan Garcia in his home studio

Dan Garcia's creative video lessons keep students engaged

CS Teaching Prof. Dan Garcia is featured in NBC Bay Area for his innovative teaching style which keep his students engaged in online learning.  He has "transformed his mancave into a studio," where he films and edits his creative virtual lessons, and then uploads them for students to watch.  Known for rapping his own lyrics to songs from the musical Hamilton in giant lecture halls, Garcia has adapted to using a green screen to film and edit his one hour video lessons, incorporating a variety of voices.  His extra efforts have been lauded by students stuck in their rooms during the fall semester.

Peter Bartlett and Bin Yu to lead $10M NSF/Simons Foundation program to investigate theoretical underpinnings of deep learning

The National Science Foundation (NSF) and the Simons Foundation Division of Mathematics and Physical Sciences are partnering to award $10 million to fund research in the Mathematical and Scientific Foundations of Deep Learning, led by CS Prof. Peter Bartlett and EECS Prof. Bin Yu.  Both professors hold joint appointments in the Department of Statistics.  The researchers hope to gain a better theoretical understanding of deep learning, which is part of a broader family of machine learning methods based on artificial neural networks that digest large amounts of raw data inputs and train AI systems with limited human supervision. Most of the research and education activities will be hosted by the Simons Institute for the Theory of Computing, in the form of structured programs of varying themes.  Other participating institutions will include Stanford, MIT, UCI, UCSD, Toyota Tech in Chicago, EPFL in Switzerland, and the Hebrew University in Israel.

Brian Harvey wins NTLS Education Technology Leadership Award

CS Teaching Prof. Emeritus Brian Harvey has been awarded the National Technology Leadership Summit (NTLS) Education Technology Leadership Award, which recognizes individuals who made a significant impact on the field of educational technology over the course of a lifetime.  The award is NTLS's highest honor.  Harvey wrote the "Computer Science Logo Style" textbook trilogy in the 1980s, which uses the Logo programming language (a subdialect of Lisp which had been created for elementary school children) to teach computer science concepts to more advanced students.   He designed UCBLogo in 1992, a free, open-source programming language that is now the de facto standard for Logo, and won the Berkeley Distinguished Teaching Award in 1995.  He then collaborated with award co-recipient Jens Möenig to develop the block programming language Snap!, which makes advanced computational concepts accessible to nonprogrammers.  It is used in the highly successful class "Beauty and Joy of Computing," which was developed at Berkeley to introduce more diverse audiences to CS. The class is approved for AP credit and, with support from the NSF, has been provided to more than one thousand high school CS teachers nationwide.  Harvey says “Languages in the Logo family, including Scratch and Snap!, take the position that we’re not in the business of training professional computer programmers. Our mission is to bring programming to the masses.”

Dick White has passed away

Prof. Richard M. White, age 90, passed away this week from complications after a fall.  Born in Colorado and educated at Harvard, White joined the EECS department in 1962 after a stint doing research at General Electric.  He was a prolific researcher, publisher and inventor, who authored or co‐authored more than 90 research papers and two books. His research on micro‐sensors and actuators making use of Surface Acoustic Wave (SAW) effects, earned him the UFFC Rayleigh Ultrasonics Award in 2003.  He founded the Berkeley Sensor and Actuator Center (BSAC) with Richard Muller in 1986, which led the creation of the field of Micro-Electromechanical Systems (MEMS), one of the key innovations pioneered in the EECS department.  BSAC currently hosts 12 faculty and more than 100 graduate students.  White and Muller earned the James Clerk Maxwell Award for their contributions to MEMS in 2013. Full of energy and ideas, White was also a passionate instructor whose forte was introducing students to electronics (he created and taught the introductory course EE 1 for many years).  He was also one of the founders of the Graduate Group in Science and Mathematics Education (SESAME), which was later absorbed into the School of Education. Just before his death, White was actively engaged in the creation of a new sensor to detect COVID-19. He leaves behind two sons, Rollie and Brendan.

Umesh Vazirani to help lead $25 million quantum computing center

The National Science Foundation (NSF) has awarded UC Berkeley $25 million over five years to help lead the establishment of a multi-university institute focused on advancing quantum science and engineering.  EECS Prof. Umesh Vazirani, who is co-director of the Berkeley Quantum Computation Center (BQIC) and leads the quantum computing effort at the Simons Institute for the Theory of Computing (SITC), will serve as co-director of the new institute.  Other participants from EECS will include Prof. Ming Wu, Prof. Shafi Goldwasser, Prof. John Kubiatowicz, and Associate Prof. Boubacar Kanté. The center will be one of three Quantum Leap Challenge Institutes (QLCI) designed as part of the federal government's effort to accelerate the development of quantum computers, train a future workforce to build and use them, and position them to be as ubiquitous as smart phones.  The new institute for Present and Future Quantum Computation will connect Berkeley, UCLA, UCSB, USC, Caltech, UT Austin, MIT, and UW, to combine the talents of top experimental and theoretical scientists in the fields of computer science, chemistry, physics, materials science, engineering and mathematics, to solve problems and devise strategies around this currently rudimentary technology.   Attaining a better understanding of its computational capabilities will require a major increase in the number of computer scientists involved in asking and answering questions.  “Realizing the full power of quantum computation requires development of efficient schemes for correction of errors during operation of quantum machines, as well as protocols for testing and benchmarking," said Vazirani. “Translating this remarkable ability of quantum computers into actually solving a computational problem is very challenging and requires a completely new way of thinking about algorithms.”

prof. david wagner

David Wagner testifies about remote voting security before Congress

Prof. David Wagner, whose area of expertise includes computer security and the security of electronic voting, testified before Congress at a hearing of the House Administration Committee on Friday, July 15, 2020. The hearing was called to investigate options for lawmakers in Congress to vote remotely during Covid-19. Wagner explained that while it is technologically feasible for the House to conduct roll-call votes remotely, it will come with some manageable risk.  He recommended securing the vote using "a combination of people, process, and technology," including making all votes public immediately, having the House establish policies to govern the process--including contingencies for technology failures, and specifically selecting technology to support cybersecurity. 

Stuart Russell answers 3+ questions in wake of Turing Lecture

In May 2020, CS Prof. Stuart Russell delivered the most highly attended Turing Lecture yet,  to a virtual audience of over 700 people from around the world, on the subject of provably beneficial AI.  In a follow-up article, "Three (plus) questions with Turing Lecturer Stuart Russell," he answers some of the many questions not covered during the live Q&A.  In his talk, Russell argues that "it is useful to imbue systems with explicit uncertainty concerning the true objectives of the humans they are designed to help. This uncertainty causes machine and human behaviour to be inextricably (and game-theoretically) linked, while opening up many new avenues for research."  The top three questions address how AI should make immediate choices, how to address changing preferences as society evolves, and how AI can be controlled to minimize bias.  The ideas discussed are explored in his most recent book, "Human Compatible: AI and the Problem of Control" (Viking/Penguin, 2019).  The Turing Lectures are hosted by The Alan Turing Institute, the UK’s national institute for data science and artificial intelligence, and should not be confused with the Turing Talks sponsored by BCS and IET.

Two EECS projects awarded Berkeley Changemaker Technology Innovation Grants

CS Prof. Eric Paulos and Associate Prof. Bjoern Hartmann have both won 2020 Berkeley Changemaker Technology Innovation Grants to support projects involving "transformative ideas with real applications that benefit the Berkeley campus."  Paulos's project is Lucid Learning, a suite of tools to help students in disciplines like architecture, art practice, theater, dance and performance studies, to incorporate augmented reality (AR) and virtual reality (VR) into their iterative processes of collaboration, design and feedback.  There are currently online tools that can help assess work in quantitative courses but few available for more open-ended, studio-based teamwork courses.  Hartmann's project, VRTutor, aims to both allow students to interact with an instructional 3D video pre-recorded by their professor in VR, and also allow instructors to view a live feed of students working in VR to give them guidance.  Tutorial feedback can be offered by drawing on the student's video feed on a tablet, then re-projecting the drawings into the student’s VR scene in 3D.

Two projects led by EECS faculty win funding to combat COVID-19

Projects led by CS Prof. Jennifer Listgarten and EE Prof. Alberto Sangiovanni-Vincentelli have been awarded funding from the Digital Transformation Institute to harness the power of AI to combat the spread of COVID-19 and other emerging diseases.  Listgarten's project will draw upon techniques such as reinforcement learning, robust uncertainty estimation and probabilistic modeling to develop new and trustworthy methods for therapeutic drug discovery for COVID-19.  Sangiovanni-Vincentelli's project will develop algorithms for AI that will help health care institutions better detect and contain emerging diseases.  These projects are two of six awarded to UC Berkeley, and among 26 projects world-wide, which will share $5.4M to accelerate AI research for COVID-19 mitigation through advances in medicine, urban planning and public policy.