EECS alumnus John Maidens (PhD 2017) and his advisor EECS Prof. Murat Arcak have won the International Federation of Automatic Control (IFAC) Automatica Paper Prize for “Symmetry Reduction for Dynamic Programming,” co-authored by Axel Barrau and Silvère Bonnabel (Automatica vol. 97, pp. 367-375, 2018).  This journal award recognizes "outstanding contributions to the theory and/or practice of control engineering or control science, documented in a paper published in the IFAC Journal Automatica," and will be presented this week at the triennial IFAC World Congress during the virtual closing ceremony.  Maidens is now a data scientist at Eko where he builds AI to automatically assess heart health.

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.

Projects led by CS Prof. Jennifer Listgarten and EE Prof. Alberto Sangiovanni-Vincentelli have been awarded funding from the C3.ai 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.

EECS Assoc. Prof. Boubacar Kanté, his graduate students Liyi Hsu, Jeongho Ha and Jun-Hee Park, postdoctoral researcher Abdoulaye Ndao, and Prof. Connie Chang-Hasnain, have demonstrated a revolutionary, ultrathin and compact, flat optical lens that spans wavelengths from the visible to the infrared with record-breaking efficiencies.  Their paper, “Octave bandwidth photonic fishnet-achromatic-metalens,” published in Nature Communications, is the first time a photonic system with the entire rainbow has been proposed and demonstrated with efficiencies larger than 70% in the visible-infrared region of the spectrum.  Attempts to make traditional lenses flatter and thinner, so that they can be deployed in increasingly smaller applications, have been hampered by the way that lens curvature and thickness are used to direct light.  The Fishnet-Achromatic-Metalens (FAM) utilizes a complex “fishnet” of tiny, connected waveguides with a gradient in dimensions, which focuses light on a single point on the other side of the lens, regardless of the incident wavelength.  As the world’s thinnest, most efficient, and broadest band, flat lens, its use in applications like solar energy, medical imaging, and virtual reality, is just the beginning.  As Kanté explains, “We have overcome what was regarded as a fundamental roadblock.”  One idea for a possible implementation would be to integrate the miniature lens into microrobots being developed at the Berkeley Sensor & Actuator Center (BSAC).

EECS Prof. and dean of the College of Engineering Tsu-Jae King Liu has won the 2020 Chang-Lin Tien Leadership in Education Award.  The award honors an Asian American and Pacific Islander (AAPI) who has achieved "significant academic accomplishments and demonstrates the potential to advance to the highest leadership levels in higher education." Recipients are awarded $10K to establish a Chang-Lin Tien Scholarship Fund for AAPI students at their university.  The award was named in honor of Berkeley ME Prof. Chang-Lin Tien, who became the first AAPI to head a major US research university when he was elected Chancellor of UC Berkeley in 1990.  “This award is especially humbling to me," said King Liu, "because Dr. Tien was Chancellor when I joined the UC Berkeley faculty in 1996. I was touched by his warmth as a human being and affection for all things related to Berkeley, and am inspired by his example to advance the university’s noble mission of research, education, and service for the betterment of society.”

CS Assistant Prof. Aditya Parameswaran has been awarded the Best Paper Award at the 2020 ACM Special Interest Group on Management of Data (SIGMOD)/Symposium on Principles of Database Systems (PODS) for his joint paper: “ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines.”  The paper proposes the implementation of ShapeSearch, a tool that mitigates issues with existing visual analytics tools, such as limited flexibility, expressiveness, and scalability.  The paper was one of two that received the top award out of over 144 accepted research papers and 450 submissions to ACM SIGMOD/PODS, the premiere international conference on the theoretical aspects of database systems.

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. 

EECS alumna and Prof. Dawn Song (Ph.D. '02) appears in episode #95 of the Artificial Intelligence Podcast with Lex Fridman to discuss adversarial machine learning and computer security.   They cover topics ranging from attacks on self-driving cars to data ownership, program synthesis, and the meaning of life.

CS Prof. Michael I. Jordan, one of the world’s foremost researchers of machine learning, has been awarded an Honorary Doctorate in Engineering and Technology from Yale University.  Since 1702, honorary degrees have been the most significant recognition conferred by Yale, and signal "pioneering achievement in a field or conspicuous and exemplary contribution to the common good." Jordan's citation reads: "Facing an uncertain and complex world, you harness the power of human and machine learning to solve daunting problems. By bridging disciplines and following your curiosity, you have made possible what was once only imagined. Explorer of new domains, champion of big ideas: in recognition of the doors you have opened and the networks you have built, we proudly bestow on you this Doctor of Engineering and Technology degree."  Jordan is known for his foundational work at the interface of computer science and statistics, and for his applied work in computational biology, natural language processing, and signal processing.

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.