EECS alumna and Assistant Teaching Prof. Gireeja Ranade (M.S. '09/Ph.D. '14, advisor: Anant Sahai), and Graduate Student Instructors (GSIs) Ritika Shrivastava, Jay Monga, Maxson Yang, Suraj Rampure and Allen Shen have won UC Berkeley Extraordinary Teaching in Extraordinary Times awards.  They are among 59 people from of pool of over 500 nominees honored at Berkeley by the Academic Senate’s Committee on Teaching for embracing the challenges posed by the 2020 COVID-19 pandemic, and engaging in or supporting excellent teaching. "These instructors and staff used innovative methods and worked beyond their traditional roles to ensure that students remained engaged and supported, and were challenged to do meaningful work under extraordinary circumstances."

Shrivastava, a fall GSI for EECS C106A/206A Introduction to Robotics, provided a warm, supportive, and positive environment for her students, developed new materials, and used tools to promote inclusiveness and overcome technological differences.  Jay Monga, also a fall GSI and lab TA for EECS 106A/206A, helped students with their lab-focused robotics class by creating a video walkthrough and slides demonstrating procedures and assignments, recording a presentation to promote asynchronous instruction, helping to design a more accessible lab, and creating a Discord server for better virtual learning. Yang, who was a summer GSI for CS 10 The Beauty and Joy of Computing,  released a comprehensive student survey to guide course policy and focused on  reducing common stressors (like deadlines), implementing weekly check-ins, and creating ways to improve the students' virtual experience (like memes).  Rampure, who was a fall GSI and summer instructor for Data C100 Principals & Techniques of Data Science, and Shen, who was a fall GSI and summer instructor for CS 186 Introduction to Data Systems, won the award together for teaching two of Berkeley’s flagship undergraduate data science courses.  They introduced new applications of course material, prioritized accessibility in lectures, designed assessments, and used real-world examples to promote engagement. 

CS Prof. and Chan Zuckerberg Biohub investigator Michel Maharbiz is the senior author of a paper in Nature Biotechnology titled "Monitoring deep-tissue oxygenation with a millimeter-scale ultrasonic implant," which describes a tiny wireless implant that can provide real-time measurements of tissue oxygen levels deep underneath the skin. The device, which is smaller than the average ladybug and powered by ultrasound waves, could help doctors monitor the health of transplanted organs or tissue and provide an early warning of potential transplant failure.  “It’s very difficult to measure things deep inside the body,” said Maharbiz. “The device demonstrates how, using ultrasound technology coupled with very clever integrated circuit design, you can create sophisticated implants that go very deep into tissue to take data from organs.”

EECS alumnus Yang You (Ph.D. '20, advisor: James Demmel) has been named in the Forbes 30 Under 30 2021 Asia list for Healthcare and Science.  Yang, who is now a Presidential Young Professor of Computer Science at the National University of Singapore, studies Machine Learning, Parallel/Distributed Algorithms, and High-Performance Computing. The focus of his research is scaling up deep neural networks training on distributed systems or supercomputers.  He has broken two world records for AI training speed: one in 2017 for ImageNet and the other in 2019 for Boundless Electrical Resistivity Tomography (BERT).  Yang has won numerous best paper awards as well as the inaugural Berkeley EECS Lotfi A. Zadeh Prize for outstanding contributions to soft computing and its applications by a graduate student.

EE alumna Leslie Field (M.S. '88/Ph.D. '91, advisor: Richard White), who is the founder and CTO of the Arctic Ice Project and an adjunct lecturer at Sanford, will be a co-panelist in a webinar titled "Reflections on Arctic Ice: A special webinar with Dr. Peter Wadhams."  Wadhams, a professor emeritus of Ocean Physics at Cambridge and the author of “A Farewell to Ice,”  has made more than 50 polar expeditions and recently appeared in the documentary “Ice on Fire” with Leonardo DiCaprio.   Field was the first woman to earn a Ph.D. from the Berkeley Sensor and Actuator Center (BSAC).  The event will be on April 20th at 12 pm PST and is free, but registration is required.

CS Assistant Prof. Rediet Abebe is co-chairing the inaugural ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO ’21) in October 2021.  This conference will highlight work where techniques from algorithms, optimization, and mechanism design, along with insights from other disciplines, can help improve equity and access to opportunity for historically disadvantaged and underserved communities.  Launched by the Mechanism Design for Social Good (MD4SG) initiative, it will feature keynote talks and panels, and contributed presentations of research papers, surveys, problem pitches, datasets, and software demonstrations.   The submission deadline is June 3, 2021.

EECS graduate student Andreea Bobu (advisor: Anca Dragan) has been named a 2021 Apple Scholar in AI and Machine Learning (AI/ML).  The scholarship was created by Apple to "celebrate the contributions of students pursuing cutting-edge fundamental and applied machine learning research worldwide."  Bobu's research interests lie at the intersection of machine learning, robotics, and human-robot interaction, with a focus in robot learning with uncertainty. She is particularly interested in the ways in which autonomous systems’ models of the world and of other agents (e.g. humans) can go wrong, and is devising ways to enhance interaction between people and robots.  She earned her BS in Computer Science and Engineering at MIT in 2017, where she worked on probabilistic models for medical image analysis.  She is currently associated with the Berkeley Artificial Intelligence Research (BAIR) lab.

EECS graduate student Wenshuo Guo (advisor: Michael I. Jordan) has won a 2021 Google PhD Fellowship in Algorithms, Optimization and Markets.  This award acknowledges and supports exemplary PhD students in computer science and related fields who are making contributions to their areas of specialty.   Guo studies robustness guarantees in algorithms and machine learning foundations, as well as their impact on society.  She is also interested in the intersection of CS and economics, and is currently focused on mechanism design, causal inference, and statistical questions in reinforcement learning. The award, which will cover full tuition, fees, and a stipend for the 2021-22 school year, will be presented at the Global Fellowship Summit over the summer.
 

CS Prof. Michael I. Jordan is the subject of an IEEE Spectrum article which describes his life, research, and philosophy.  A computer science pioneer, Jordan blended CS, statistics, and applied mathematics, to help transform unsupervised machine learning into a powerful algorithmic tool for solving problems in fields like natural language processing, computational biology, and signal processing.  He explains that machine learning is, in essence, a new field of engineering focused on the interface between people and technology.  The optimal goal of machine learning should not be artificial imitation of human thinking since that is something human beings can already do for themselves.  Instead, AI should be focused on helping humanity solve the problems that it has created.  “While the science-fiction discussions about AI and super intelligence are fun, they are a distraction,” Jordan says. “There’s not been enough focus on the real problem, which is building planetary-scale machine learning–based systems that actually work, deliver value to humans, and do not amplify inequities.

CS Assistant Prof. Rediet Abebe is the subject of a profile in Quanta Magazine which describes how she uses the tools of theoretical computer science to understand pressing social problems -- and try to fix them.   Abebe, who is from Ethiopia, earned a B.A. in mathematics from Harvard, attended a one-year intensive math program at Cambridge, and switched to Computer Science at Cornell where she earned her Ph.D.   She was drawn to CS because it allowed her to apply mathematical thinking to social problems like discrimination, inequity and access to opportunity.  Abebe has co-founded two organizations: Black in AI, a community of Black researchers working in artificial intelligence, and Mechanism Design for Social Good, which brings together researchers from different disciplines to address social problems. The Q&A interview discusses her life and career choices, as well as her research and its applications.

CS Prof. Joseph Hellerstein has been named a Datanami 2021 Person to Watch.  Hellerstein is the chief strategy officer and one of the co-founders  a Trifacta, a company which markets data preparation and interaction technology based on Data Wrangler, a data transformation and discovery tool he developed in the RISELab at Berkeley with some colleagues from Stanford.  He is the subject of a Datanami article in which he discusses the state of data science education, the next wave of data, and the secrets of his success.