CS Prof. Hany Farid is leaving Dartmouth, where he taught for 20 years, to take up a faculty position in the EECS department.  Farid specializes in digital forensics and image analysis. Some of his most well-known projects have applied computer science to test whether images have been doctored, using his expertise to tackle issues such as crime prevention, child pornography and scientific integrity.  “There are a lot of opportunities, given the scale of Berkeley, for things that I can do there that I’m really excited about,” he said.  Farid is best known to Dartmouth students as a favorite professor in the introductory computer science course, Computer Science 1: Introduction to Programming and Computation.  He sees teaching as his way of making a lasting impact.  “Do a good job in the classroom, inspire somebody, change the way they think, you’re affecting the next 50 years of their life.”

CS Prof. Eric Paulos and his graduate students in the Hybrid Ecologies Lab, Sarah Sterman, Molly Nicholas, and Christine Dierk, have created a prototype of a wearable color- and shape-changing braid called HäirIÖ.  The hair extension is built from a custom circuit, an Arduino Nano, an Adafruit Bluetooth board, shape memory alloy, and thermochromic pigments.  The bluetooth chip allows devices such as phones and laptops to communicate with the hair, causing it to change shape and color, as well as respond when the hair is touched. Their paper "Human Hair as Interactive Material," was presented at the ACM International Conference on Tangible, Embedded and Embodied Interaction (TEI) last week. They have posted a how-to guide and instructable videos which include comprehensive hardware, software, and electronics documentation, as well as information about the design process. "Hair is a unique and little-explored material for new wearable technologies," the guide says.  "Its long history of cultural and individual expression make it a fruitful site for novel interactions."

A new Data Science major in the College of Letters and Science has been approved, effective Fall 2018. This is part of Berkeley’s active engagement with the burgeoning field of data science, which has the potential to shape numerous fields of study and practice.  The major is designed to equip students to draw sound conclusions from data in context, using knowledge of statistical inference, computational processes, data management strategies, domain knowledge, and theory.  Students will learn to carry out analyses of data through the full cycle of the investigative process in scientific and practical contexts, as well as gain an understanding of the human and ethical implications of data analysis and integrate that knowledge into their work.   The College of Engineering also has plans for a Data Science major, which is currently undergoing design and review.  A minor is also under consideration for students in both colleges. More than 3,000 students enroll in data science courses at Berkeley every year.

2018 EE Distinguished Alumna Andrea Goldsmith (B.A. ’86/M.S. ’91/Ph.D. ’94) has been named the 2018-19 Association for Computing Machinery (ACM) Athena Lecturer for contributions to the theory and practice of adaptive wireless communications, and for the successful transfer of research to commercial technology.  Goldsmith, who is currently the Stephen Harris Professor in the School of Engineering at Stanford,  introduced innovative approaches to the design, analysis and fundamental performance limits of wireless systems and networks. The Athena Lecturer Award, which was initiated by the ACM Council on Women in Computing (ACM-W), celebrates women researchers who have made fundamental contributions to computer science. The award carries a cash prize of $25,000, with financial support provided by Google.

In an Op-Ed piece for Medium, CS and Statistics Prof. Michael Jordan examines the limits of AI and argues for the creation of an engineering discipline encompassing data science, intelligent infrastructure (II), and intelligence augmentation (IA).   Principles of analysis and design must be applied when building planetary-scale inference-and-decision-making systems because they will have a profound effect on human lives.   "We need to realize that the current public dialog on AI — which focuses on a narrow subset of industry and a narrow subset of academia — risks blinding us to the challenges and opportunities that are presented by the full scope of AI, IA and II," he writes.

EECS Chair Prof. James Demmel (Ph.D. '83) and CS Prof. Emeritus Eric Brewer (B.S. '89) have been elected to the American Academy of Arts and Sciences. The academy is one of the oldest learned societies in the United States and serves the nation as a champion of scholarship, civil dialogue and useful knowledge.  Members are nominated and elected by peers, and membership has been considered a high honor of scholarly and societal merit ever since the academy was founded in 1780. Demmel, who holds joint appointments in the EECS Department and the Department of Mathematics, won the ACM Paris Kannelakis Theory and Practice Award in 2014 and the IEEE Computer Society Sydney Fernbach Award in 2010 for "computational science leadership in creating adaptive, innovative, high performance linear algebra software." Brewer, who now serves as VP of Infrastructure at Google, is one of the 2018 CS Distinguished Alumni as well as the 2009 recipient of the ACM Prize in Computing for his "design and development of highly scalable internet services and innovations in bringing information technology to developing regions"

EECS graduate student Michael Laskey (advisor: Ken Goldberg) is interviewed by Audrow Nash for a Robohub podcast titled "DART: Noise injection for robust imitation learning."  Laskey works in the AUTOLAB where he develops new algorithms for Deep Learning of robust robot control policies and examines how to reliably apply recent deep learning advances for scalable robotics learning in challenging unstructured environments.  In the podcast, he discusses how DART relates to previous imitation learning methods, how this approach has been used for folding bed sheets, and on the importance of robotics leveraging theory in other disciplines.

EECS alumna Lea Kissner (B.S. '02) is the subject of a Gizmodo article describing her visit to a class at Berkeley this week where she discussed her job as a Principal Engineer at Google leading the security and privacy teams for infrastructure and social products.  One team of 90 employees with different backgrounds and skill sets, called NightWatch, reviews almost all of the products that Google launches for potential privacy flaws.  The article also covers some of the obstacles she has faced and her involvement chairing a discussion topic on Practical Privacy Protection at the OURSA conference in San Francisco today. “I want to tell people things we’ve learned. I want to build the world I want to live in, and the world I want to live in includes things like products being designed respectfully of users and systems being designed respectfully for users. I don’t think everybody has to learn everything the hard way,” Kissner tells me later. Then, the mathematician in her kicks in and she adds, “It’s very inefficient if nothing else.”

CS graduate student Allan Jabri has been named a 2018 Paul & Daisy Soros Fellow.   Soros Fellowships are awarded to outstanding immigrants and children of immigrants from across the globe who are pursuing graduate school in the United States.  Recipients are chosen for their potential to make significant contributions to US society, culture, or their academic fields, and will receive up to $90K in funding over two years.  Jabri was born in Australia to parents from China and Lebanon and was raised in the US.   He received his B.S. at Princeton where his thesis focused on probabilistic methods for egocentric scene understanding, and worked as a research engineer at Facebook AI Research in New York before joining Berkeley AI Research (BAIR).  He  is interested in problems related to self-supervised learning, continual learning, intrinsic motivation, and embodied cognition. His long-term goal is to build learning algorithms that allow machines to autonomously acquire visual and sensorimotor common sense. During his time at Berkeley, he also hopes to mentor students, contribute to open source code projects, and develop a more interdisciplinary perspective on AI.

EECS instructional system administrator Linda Huang (who publishes under the name Yang Huang) has just released her second book, a collection of short stories titled "My Old Faithful: Stories" (University of Massachusetts Press).   The ten interconnected stories, which take place in China and the United States over a thirty-year period, merge to paint a nuanced portrait of family life, full of pain, surprises, and subtle acts of courage. Richly textured narratives from the mother, father, son, and daughters of a close-knit Chinese family play out against the backdrop of China's social and economic change.  "My Old Faithful" won the 2017 Juniper Prize for Fiction , an award established by the University of Massachusetts Press to honor outstanding novels and short story collections.  Mrs. Dalloway's bookstore in Berkeley is hosting an event, "Yang Huang in Conversation with Kaitlin Solimine," on Thursday, April 26 at 7:30 pm.  Huang's debut novel, "Living Treasures," won the Nautilus Book Award Silver Medal in Fiction in 2014.