honors

Honors, awards, grants, and other indications of respect.

Michael Jordan wins 2021 AMS Ulf Grenander Prize

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.

Dawn Song wins 2020 ACM SIGSAC Outstanding Innovation Award

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.

Ali Niknejad wins 2020 SIA University Research Award

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.

Natacha Crooks wins 2020 ACM SIGOPS Dennis M. Ritchie dissertation award

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.

Gabe Fierro wins inaugural Google - CMD-IT FLIP Dissertation Fellowship

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" chosen as ISMRM Reproducible Research pick

"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.

Mike Stonebraker wins 2020 C&C Prize

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.

Ali Niknejad wins SIA 2020 University Research Award

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.

Dorsa Sadigh wins 2020 IEEE TCCPS Early Career Award

EECS alumna Dorsa Sadigh (BS '12 / PhD '17, advisors: Shankar Sastry and Sanjit Seshia) has been recognized with the IEEE Technical Committee on Cyber-Physical Systems (TCCPS) Early Career Award ‘‘for contributions to the theory, design, and implementation of human cyber-physical systems.’’ She is currently an Assistant Professor in the Departments of both Computer Science and Electrical Engineering at Stanford University.  Her research interests lie at the intersection of robotics, machine learning, and control theory, and she is currently working on developing efficient algorithms for safe, reliable, and adaptive human-robot and generally multi-agent interactions.

Kathy Yelick wins 2020 Berkeley Lab Citation for Exceptional Achievement

EECS Prof. Katherine Yelick has won The Berkeley Lab Citation, the Lawrence Berkeley National Laboratory (LBNL) Director's Award for Exceptional Achievement which "honors extraordinary achievement(s) in broad categories of science and operations, with special focus on service to the Lab and/or the DOE National Lab Complex."  Yelick was cited for "extraordinary leadership both within the Lab and at the national level, including her significant role in developing DOE strategy in Exascale and Quantum Computing, Big Data, and Artificial Intelligence."  Yelick is the Senior Advisor on Computing at LBNL and the Associate Dean for Research in UC Berkeley's new Division of Computing, Data Science and Society (CDSS).  She was the Associate Laboratory Director for Computing Sciences at LBNL from 2010 through 2019, and led the National Energy Research Scientific Computing Center (NERSC) prior to that.  Her research focuses on high performance computing, programming languages, compilers, parallel algorithms, and automatic performance tuning. She currently leads the ExaBiome project on scalable tools for analyzing microbial data and co-leads the Berkeley Benchmarking and Optimization (Bebop) group.