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).

EECS alumnus Michael Athans (B.S. '58/M.S. '59/Ph.D. '61, adivsor: Otto J. M. Smith), a pioneer in the field of control theory, has died at the age of 83.   Athans, who was born in Greece and graduated under the surname Athanassiades, had been a professor of electrical engineering at MIT for 34 years before retiring in 1998.  He helped shape modern control theory by developing central methodologies geared toward large-scale systems, which broadened the scope of the field, and helped spearhead the area of multivariable control system design and the field of robust control.  He became the director of the MIT Electronic Systems Laboratory in 1974, and renamed it the Laboratory for Information and Decision Systems (LIDS) four years later, reflecting the lab’s expansion into new domains like transportation, energy, and economics.  Athans was also an award-winning educator, supervising the theses of more than 100 graduate students, producing nearly 70 videotaped lessons for practicing engineers, developing coursework, and co-authoring three books, including the foundational text “Optimal Control" (with Peter Falb).

EECS alumnus Gary S. May (M.S. '88/Ph.D. '91, advisor: Costas Spanos), the first Black chancellor of UC Davis, has penned an op-ed for the San Francisco Chronicle titled "UC Davis chancellor: George Floyd could have been me" in which he observes that "at a traffic stop, no one knows I am a chancellor. No one knows I have a doctorate."  He explains that building an inclusive society that recognizes and respects people of all socioeconomic and cultural backgrounds, and a wide variety of political views, gender identities, and personal experiences, will increase our capacity to "make discoveries and solve problems."  "It requires collective effort," he writes.  "It requires each one of us, in our own way, working to make a difference, whether that’s through video recording, peaceful protest or working to change procedures that reflect bias."

EECS alumna Olivia Hsu (B.S. '19) will be giving a speech at the national 2020 IEEE-Eta Kappa Nu (HKN) virtual graduation celebration on Saturday, May 30, 2020.  Hsu is the winner of the 2019 IEEE-HKN Alton B. Zerby and Carl T. Koerner Outstanding Electrical or Computer Engineering Student of the Year Award, and is the representative for the Mu (Berkeley) Chapter, which has won the IEEE-HKN Outstanding Chapter Award every year since 2001.   While at Berkeley, Hsu co-founded the student group Space Technologies at Cal (STAC) and won the 2019 EECS Arthur M. Hopkin award, which recognizes outstanding EE undergraduates who "demonstrate seriousness of purpose and high academic achievement."  She is currently pursuing a Ph.D. at Stanford with a focus on computer architecture, digital circuits, and computer systems.  IEEE-HKN will host the event for the first time this year in place of the campus commencement ceremonies which  have been cancelled nationwide. 

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 alumnus Mark Hopkins (B.A. CS '00) has been appointed to a tenure-track position in the department of Computer Science at Reed College in Oregon. He will be part of the division of Mathematical and Natural Resources where he will study uncertain reasoning and machine learning, with a particular interest in how these can be applied to computational linguistics.  Hopkins earned his Ph.D. from UCLA in 2005 and had managed Project Euclid at the Allen Institute of Artificial Intelligence (AI2) in Washington state before being hired as a visiting associate professor at Reed in 2018.

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.

EECS alumna Andrea Goldsmith (B.A. ’86/M.S. ’91/Ph.D. ’94, advisor: Pravin Varaiya), who was named Berkeley EE Distinguished Alumna in 2018, has been named dean of Princeton University’s School of Engineering and Applied Science.  Goldsmith has been a professor of electrical engineering at Stanford since 1999 and is a leader in the fields of information theory and communications. She helped lay the mathematical foundations for increasing the capacity, speed and range of wireless systems, and among her 29 patents are many inventions central to cell phone and Wi-Fi networks.  Earlier this month, Goldsmith became the first woman to win the Marconi Prize, said to be the highest honor in telecommunications research.  She has also been active in efforts to increase diversity in STEM fields and is the founding chair of the IEEE Board of Directors Committee on Diversity, Inclusion and Ethics.  When she starts her tenure as dean in September, she will oversee a school comprising six departments and four research centers, including new initiatives in bioengineering, data science and robotics, among others.

Alumnus Courtney Brousseau (B.A. CS/Econ '19) has died after  being injured as a bystander in a drive-by shooting in the Mission District of San Francisco.  Brousseau was an active member of the Berkeley community while a student, serving as a CS tutor and acting as chair of the ASUC Student Union.  After graduation, he worked as a Civic Digital Fellow at Coding it Forward in Washington, D.C.,  and was hired as an Associate Product Manager at Twitter last fall.  He also founded an advocy group called Gay for Transit in an effort to improve conditions for bicyclists and make San Francisco streets safer.

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.”