The creators of BerkeleyDB (BDB) have won the 2020 Association for Computing Machinery (ACM) Special Interest Group on Management of Data (SIGMOD) Systems Award for their "seminal work in embodying simplicity, quality, and elegance in a high-performance key-value store that has impacted many systems and applications over the last 25 years."   BDB is a software library that originated as an effort to free up the user space utilities in BSD, UC Berkeley's free version of the Unix operating system.  It used revolutionarily simple function-call APIs for data access and management, which allowed developers to create custom solutions at a fraction of the usual cost.  Keith Bostic, a member of Berkeley's Computer Science Research Group (CSRG), and his wife, graduate student Margo Seltzer (Ph.D. '92, advisor: Michael Stonebraker), co-founded Sleepycat Software, Inc. to provide commercial support for BDB.  Seltzer served as CTO, Bostic as VP Eng and Product Architect, and former Berkeley student and BDB co-developer Mike Olson (who later co-founded Cloudera) was the first full-time employee and later served as CEO.  Seltzer, Bostic, and Olson are among the 16 developers cited for the award. BDB ships in every copy of Linux and BSD; drove most LDAP servers, and powered a large portion of the Web 1.0.

EECS alumna Ming C. Lin (B.S./M.S./Ph.D. '93, advisor: John Canny) has been elected to the Association for Computing Machinery (ACM) Special Interest Group on Graphics and Interactive Techniques (SIGGRAPH) Academy.  She is one of six scholars selected for membership this year, an honor which is reserved for individuals who have made "substantial contributions to the field."  Lin was cited "for contributions in collision detection, physics simulation, natural phenomena, crowd animation, haptics, and sound rendering."  She became an ACM Fellow in 2011 and IEEE Fellow in 2012, and is currently chair of the Computer Science department at the University Maryland.  An expert in virtual reality, computer graphics and robotics, Lin's particular focus is on multimodal interaction, physically based animations and simulations, as well as algorithmic robotics and their use in physical and virtual environments.  Her research has applications in medical simulations, cancer screening, urban computing, as well as supporting city-scale planning, human-centric computing, intelligent transportation and traffic management.

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).

Eden McEwen, a fourth year undergraduate double-majoring in Computer Science and Physics, has been awarded a 2020 Optics and Photonics Education Scholarship by the international Society of Photo-Optical Instrumentation Engineers (SPIE), for her potential contributions to the field of optics and photonics.  McEwen's research interests focus on predictive control and hardware design of adaptive optics systems for ground based astronomical observing in the optical and near-infrared. She has worked with groups at Berkeley, Keck II Observatory, NASA JPL, Caltech, and the University of Hawaii’s Institute for Astronomy. McEwen is a 2020 Goldwater Scholar and hopes to continue her studies in optics with a graduate degree in astrophysics.

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.

Incoming CS graduate student Meena Jagadeesan has won a 2020 Paul & Daisy Soros Fellowship for New Americans.  The fellowship program honors the contributions of immigrants and children of immigrants to the United States by investing in the education of a select group of new Americans who are "poised to make significant contributions to US society, culture or their academic field." Jagadeesan, whose parents emigrated from India, is a senior in a joint B.A./M.A. program at Harvard University where she is studying algorithmic questions, especially those arising in machine learning and economics.  She has won a CRA Outstanding Undergraduate Researcher award and one of her papers, which involved the study of a dimensionality reduction scheme, was selected as an oral presentation at the Conference on Neural Information Processing Systems (NeurIPS).  Each Fellow will receive up to $90K in financial support over two years.

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.