CS Prof. Michael I. Jordan has been awarded the 2021 American Mathematical Society (AMS) Ulf Grenander Prize in Stochastic Theory and Modeling.   The prize, which was established in 2016, recognizes "exceptional theoretical and applied contributions in stochastic theory and modeling." It is awarded for "seminal work, theoretical or applied, in the areas of probabilistic modeling, statistical inference, or related computational algorithms, especially for the analysis of complex or high-dimensional systems." Jordan, who has a split appointment in Statistics, was cited for "foundational contributions to machine learning, especially unsupervised learning, probabilistic computation, and core theory for balancing statistical fidelity with computation."  He is known for his work on recurrent neural networks as a cognitive model in the 1980s, formalizing various methods for approximate interference, and popularizing Bayesian networks and the expectation-maximization algorithm in machine learning.  The prize is awarded every three years, making Jordan the second recipient of the honor.

CS Prof. and alumna Dawn Song (Ph.D. '02, advisor: Doug Tygar) has won the 2020 ACM Special Interest Group on Security, Audit and Control (SIGSAC) Outstanding Innovation Award.  This award recognizes "outstanding and innovative technical contributions to the field of computer and communication security that have had lasting impact in furthering or understanding the theory and/or development of commercial systems."  Song was cited "for contributions to systems and software security, in particular, dynamic taint analysis for vulnerability discovery and malware detection."  She pioneered the BitBlaze Binary Analysis Infrastructure, a unified binary program analysis platform used to provide novel solutions to computer security problems, including automatic vulnerability discovery and defense, in-depth malware analysis, and automatic extraction of security models for analysis and verification.

EECS alumnus and Prof. Ali Niknejad (M.S. '97/Ph.D. '00, advisor: Robert Meyer) has won the 2020 Semiconductor Industry Association (SIA) University Research Award.  This award recognizes researchers in both technology and design who have made “a lifetime of great impact to the semiconductor industry.”  Niknejad was cited for “noteworthy achievements that have advanced analog, RF, and mm-wave circuit design and modeling, which serve as the foundation of 5G+ technologies.”  Stanford ME Prof. Kenneth Goodson also won the award this year.  “Research is the engine of innovation in the semiconductor industry, enabling breakthroughs that power our economy and help solve society’s great challenges,” said John Neuffer, SIA president and CEO. “The work of Drs. Goodson and Niknejad has greatly advanced chip technology and helped keep America at the leading edge of innovation.”  Niknejad, who previously received the 2012 ASEE Frederick Emmons Terman Award for his textbook on electromagnetics and RF integrated circuits, will accept the SIA award during the 2020 SIA Leadership Forum and Award Celebration on November 19th.

CS Assistant Prof. Natacha Crooks has won the 2020 ACM Special Interest Group on Operating Systems (SIGOPS) Dennis M. Ritchie dissertation award for her thesis titled "A Client-Centric Approach to Transactional Datastores."  The award, which recognizes creative research in software systems, was bestowed upon a dissertation which a colleague described as "a landmark, with deep and beautiful results in transactions and distributed consistency, and systems that exploit them."  The award committee commented that "Natacha Crooks’ thesis achieves something rare: a new conceptual framework for client-centric consistency and two efficient systems built on those insights. The document for this attractive package is accessible (in part) to undergraduates and the advanced material is very clearly written. With the enduring popularity of consistency as a research topic in distributed systems for the past several decades it is surprising that a breakthrough as large as Natacha’s took as long as it did."  The work was done at the University of Texas, Austin, advised by Lorenzo Alvisi and Simon Peter.

The Center for Energy Efficient Electronics Science (E3S) Transfer-to-Excellence (TTE) research program is a competitive merit-based program that offers California community college students research opportunities at Berkeley in an effort to encourage them to transfer to a university to purse a Bachelor's degree in science and engineering.  A review of the current activities of the 2019 TTE cohort, whose members received ongoing mentorship over the past year through the TTE online mentoring program, shows that all of the interns are enrolled in science or engineering academic programs and working towards a Bachelor’s degree.  Among them:

Jared Brown (TTE project advisor: EECS Prof. Sayeef Salahuddin), who transferred from Los Angeles Pierce College to UCLA to study mechanical engineering, and is active in the UCLA Samueli Center for Excellence in Engineering and Diversity; Jose Camacho (advisor: EECS Prof. Ming Wu), who transferred from Los Angeles Trade Technical College to  UC San Diego to study Electrical Engineering; Saifuddin Mohammed (advisor: EECS Chair Jeff Bokor), who transferred from Foothill College to UC Berkeley to study EECS after having received the award for best engineering poster presentation at the 2019 SACNAS Diversity in STEM conference, and completing a research internship at LBNL;  current EECS undergrad Harutyun Rehanyan (advisor: ME Prof. Shawn Shadden), who transferred to Berkeley from Los Angeles Valley College after completing a research internship at Cal State Northridge, a software engineering internship with NASA JPL, and summer research at CMU’s Institute for Software Research; and current EECS undergrad Dao Dai (David) Tran (advisor: ME Prof. Shawn Shadden), who transferred from Orange Coast College to Berkeley after completing a software engineering internship at NASA JPL and a research internship at the University of Maryland in machine learning and artificial intelligence.

EECS Chair Jeffrey Bokor is among an international team of researchers who have published a paper in the journal Nature Electronics that describes a new technique for magnetization switching — the process used to “write” information into magnetic memory — that is nearly 100 times faster than state-of-the-art spintronic devices. The advance could lead to the development of ultrafast magnetic memory for computer chips that would retain data even when there is no power.  In "Spin–orbit torque switching of a ferromagnet with picosecond electrical pulses," researchers report using extremely short, 6-picosecond electrical pulses to switch the magnetization of a thin film in a magnetic device with great energy efficiency. A picosecond is one-trillionth of a second.  The project began at UC Berkeley when Jon Gorchon, now a researcher at the French National Centre for Scientific Research (CNRS) working at the University of Lorraine L’Institut Jean Lamour in France, and Richard Wilson, now assistant professor of both mechanical engineering and materials science & engineering at UC Riverside, were postdoctoral researchers in Bokor’s lab.

EECS graduate student Gabriel Fierro (B.S. c. 2014, Ph.D. advisor: David Culler) has won an inaugural Google - CMD-IT FLIP Dissertation Fellowship.   He is one of 11 computer science scholars from underrepresented groups who were recognized this year for "positively influencing the direction and perspective of technology."   The award is part of a joint effort by Google Research, the Computing Alliance of Hispanic-Serving Institutions (CAHSI), and the Center for Minorities and People with Disabilities in Information Technology (CMD-IT) Diversifying Future Leadership in the Professoriate (FLIP) Alliance to increase the diversity of doctoral graduates in computing.  After completing his Ph.D., Fierro aspires to "a faculty position in a computer science department where I am able to pursue non-traditional and cross-disciplinary approaches to long-standing problems of sustainability and the built environment."  Fierro is currently working on the Buildings, Energy and Transportation Systems project in conjunction with the RISE Lab.

"Extreme MRI: Large‐scale volumetric dynamic imaging from continuous non‐gated acquisitions,” a paper by EECS alumnus Frank Ong (B.S. '13, Ph.D. '18) and his advisor, Prof. Miki Lustig, has been chosen as October's Reproducible Research pick by the International Society for Magnetic Resonance in Medicine (ISMRM).  The paper, in which the researchers attempt to reconstruct a large-scale dynamic image dataset while pushing reconstruction resolution to the limit, was chosen "because, in addition to sharing their code, the authors also shared a demo of their work in a Google Colab notebook."  Lustig and Ong, now a research engineer at Stanford, participated in a Q&A in which they discussed how they became interested in MRI, what makes Extreme MRI "extreme," the culture and value of open science, and why Lustig's grad school paper on compressed sensing became the most cited paper in MRM.  ISMRM is an international nonprofit association that promotes research development in the field of magnetic resonance in medicine to help facilitate continuing education in the field.

EECS Prof. Emeritus Michael Stonebraker has won the prestigious NEC Computers and Communications (C&C) Prize "For Pioneering Contributions to Relational Database Systems." The prize is awarded "to distinguished persons in recognition of outstanding contributions to research and development and/or pioneering work in the fields of semiconductors, computers, and/or telecommunications and in their integrated technologies."  In the early 1970's, Stonebraker and Prof. Eugene Wong began researching Relational Database Management Systems (RDBMS), which culminated in the creation of the Interactive Graphics and Retrieval System (INGRES), a practical and efficient implementation of the relational model running on Unix-based DEC machines.  It included a number of key ideas still widely used today, including B-trees, primary-copy replication, the query rewrite approach to views and integrity constraints, and the idea of rules/triggers for integrity checking in an RDBMS.  Stonebraker, Wong, and Prof. Larry Rowe, founded a startup called Relational Technology, Inc. (renamed Ingres Corporation), which they sold to Computer Associates in the early 1990's for $311M.  Stonebraker's student, Robert Epstein (Ph.D. '80), founded the startup Sybase, which created the code used as a basis for the Microsoft SQL Server.  Stonebraker also created Postgres in the late 1980's, which made it easier for programmers to modify or add to the optimizer, query language, runtime, and indexing frameworks.  It broadened the commercial database market by improving both database programmability and performance, making it possible to push large portions of a number of applications inside the database, including geographic information systems and time series processing.  Stonebraker retired from Berkeley in 2000 to found more companies and become an adjunct professor at MIT.  His achievements have been recognized with an IEEE John von Neumann Medal in 2005, ACM A.M. Turing Award in 2014, and ACM SIGMOD Systems Award in 2015.

EE alumnus and Prof.  Ali Niknejad (M.S. '97 / Ph.D. '00, advisor:  Robert G. Meyer ) has been selected to receive a Semiconductor Industry Association (SIA) 2020 University Research Award.  This award recognizes lifetime research contributions to the U.S. semiconductor industry by university faculty.  Niknejad is faculty director of the Berkeley Wireless Research Center (BWRC), co-founder of HMicro, chief technologist at LifeSignals, and the inventor of the REACH™ technology, which has the potential to deliver robust wireless solutions to the healthcare industry. His general research interests lie within the area of wireless communications and biomedical sensors and imaging. His focus areas of his research include analog, RF, mixed-signal, mm-wave circuits, device physics and compact modeling, and numerical techniques in electromagnetics.