Prof. Randy Katz has been inducted into the Silicon Valley Engineering Hall of Fame "for his contributions to storage and computer systems, distinguished national service, and by his exemplary mentorship and teaching that have contributed to the Silicon Valley technical community and industries."  Katz, who is also an alumnus (M.S. '78/Ph.D. '80), co-developed the redundant array of inexpensive disks (RAID) concept for computer storage along with Prof. Emeritus David Patterson and fellow alumnus Garth Gibson, in their 1988 SIGMOD Conference paper "A Case for Redundant Arrays of Inexpensive Disks (RAID)."  Silicon Valley Engineering Council (SVEC) Hall of Fame inductees have demonstrated significant engineering or technical achievements, provided significant guidance in new and developing fields of engineering-based technology, and/or have managed or directed an organization making noteworthy contributions in design, manufacturing, production, or service through the uses of engineering principles and applications.

Prof. Thomas Budinger has won the 2018 Institute of Electrical and Electronics Engineers (IEEE) Medal for Innovations in Healthcare Technology.  The award is presented "for exceptional contributions to technologies and applications benefitting healthcare, medicine, and the health sciences."  Budinger, who was the founding chair of the Bioengineering department, a division director at LBNL and Director of the Magnetic Resonance Science Center at UCSF,  is cited “For pioneering contributions to tomographic radiotracer imaging."

Prof. Eli Yablonovitch has been awarded the 2018 Institute of Electrical and Electronics Engineers (IEEE) Edison Medal.  Named for Thomas Edison and presented since 1909, the IEEE Edison Medal is awarded for a career of meritorious achievement in electrical science, electrical engineering, or the electrical arts.  Yablonovitch, who co-founded the field of of photonic crystals, was cited for "For leadership, innovations, and entrepreneurial achievements in photonics, semi-conductor lasers, antennas, and solar cells.”

Profs. Pieter Abbeel and Sanjit Seshia have been elected fellows of the Institute of Electrical and Electronics Engineers (IEEE) class of 2018.  The objectives of the IEEE, the world's largest association of technical professionals, are the educational and technical advancement of electrical and electronic engineering, telecommunications, computer engineering and allied disciplines.  The Fellow grade is the highest level of membership and is conferred by the IEEE Board of Directors in recognition of a high level of demonstrated extraordinary accomplishment.  Abbeel was selected "for contributions to apprenticeship and reinforcement learning for robotics and autonomous systems" and Seshia was selected for "for contributions to formal methods for inductive synthesis and algorithmic verification."

EECS alumnus Warren “Woody” Hoburg (MS'11, Ph.D.'13) was named R&D Magazine’s 2017 Innovator of the Year at the 55th annual R&D 100 Awards last Friday.  Hoburg recently left  his position as an assistant professor of Aeronautics and Astronautics at MIT when he was selected by NASA to join the 2017 Astronaut Candidate Class.  At MIT, Hoburg led a team that created an inexpensive, unpiloted aerial vehicle (UAV) that can keep itself aloft for more than five days — longer than any gasoline-powered autonomous aircraft has remained in flight. The technology, which has a variety of applications including providing wide-ranging communications support in the event of a natural disaster, is currently under development for the U.S. Air Force.

CS Prof. Bernd Sturmfels has won the 2018 George David Birkhoff Prize in Applied Mathematics for "his instrumental role in creating the field of applied algebraic geometry." This prize is jointly awarded by the American Math Society (AMS) and the Society for Industrial and Applied Math (SIAM) every 3 years for "an outstanding contribution to applied mathematics in the highest and broadest sense." Previous winners include Emmanuel Candes, Bjorn Engquist, and many other luminaries.

The life and contributions of CS Prof. Ruzena Bajcsy are profiled in a Philadelphia Inquirer article titled "Philly honors experts in robotics, genetics, evolution."  Bajcsy, who helped launch the field of computer vision, is being presented with a John Scott Award in science and medicine at the American Philosophical Society this evening.  Her early research paved the way for medical imaging such as MRIs, and she is noted for her cross-disciplinary approach, applying theories from mathematics and biology to her work.  She has devoted her life to research in the fields of robotics, artificial intelligence and machine perception, and took the helm of the Center for Information Technology Research in the Interest of Society (CITRIS) from 2001 to 2005.  Recipients of the Scott Awards are chosen each year based on recommendations from a panel of scientists. The award comes with a $10K prize.

Grad student Yang You, Prof. James Demmel and Prof. Kurt Keutzer, along with Prof. Cho-Jui Hsieh of UC Davis and Dr. Zhao Zhang of the Texas Advanced Computing Center (TACC), have created, in collaboration with researchers at NVIDIA, a new algorithm which enables them to harness the power of supercomputers to train a deep neural network (DNN) for image recognition at record speed. Deep learning researchers currently use trial-and-error to design new models, requiring them to run training processes tens or even hundreds of times for each model.  The team's effort efficiently used 1024 Skylake processors on the Stampede2 supercomputer at TACC to complete a 100-epoch ImageNet training with AlexNet in 11 minutes - the fastest time recorded to date.  Also, using 1600 Skylake processors, they bested Facebook's prior results by finishing a 90-epoch ImageNet training with ResNet-50 in 32 minutes and, for batch sizes above 20,000, their accuracy was much higher than Facebook's.   The group's breakthrough involved the development of the Layer-Wise Adaptive Rate Scaling (LARS) algorithm that is capable of distributing data efficiently to many processors to compute simultaneously using a larger-than-ever batch size (up to 32,000 items). The LARS algorithm was jointly developed with Nvidia. The findings show an alternative to the trend of using specialized hardware - either GPUs, Tensor Flow chips, FPGAs or other emerging architectures—for deep learning. The team wrote the code based on Caffe and utilized Intel-Caffe, which supports multi-node training. The results are published in Arxiv.

The School of Information (I School) is now accepting applications for its new, online Master of Information and Cybersecurity (MICS) program, also known as cybersecurity@berkeley.  MICS is an accredited program designed to train students with professional experience for a career in cybersecurity. Delivered online, MICS provides the technical skills and contextual knowledge students need to assume leadership positions in private sector technology companies as well as government and military organizations.  The program was developed in partnership with the College of Engineering and in collaboration with the Center for Long-Term Cybersecurity (CLTC).  A number of EECS faculty are involved with the CLTC, which seeks to create effective dialogue among industry, academia, policy makers, and practitioners around a future-oriented conceptualization of cybersecurity — what it could imply and mean for human beings, machines, and the societies that will depend on both.  The first application deadline is January 30, 2018, and the first cohort of students will begin classes in May 2018.

UC Berkeley is ranked #3 overall in the U.S. and global computer science rankings (CSRankings) for 2017.  CSRankings is designed as a more meaningful and transparent alternative to the US News and World Report computer science ranking system--which is entirely reputation-based and relies on surveys sent to department heads and directors of graduate studies.  The CSRankings system is entirely metrics-based: it weighs departments by their presence at the most prestigious publication venues.    Berkeley ranked in the top 10 in all 4 fields:  Theory (1), Artificial Intelligence (3), Systems (6) and Interdisciplinary Areas (6).  And of the 26 areas ranked, Berkeley made the top 10 in 11 of them: computer vision(2), robotics(2), machine learning and data mining(3), computer security(3), cryptography(3), design automation(3), operating systems(4), natural language processing(5), software engineering(6), algorithms & complexity(7), computer networks(8).