Several thousand leading professionals from top Silicon Valley companies are gathering in Santa Clara this evening for a banquet honoring this year's Women of Vision award recipients.
The annual event is organized by the Anita Borg Institute, one of Silicon Valley's oldest professional organizations. [Please see my interview with director Telle Whitney.]
Jennifer Chayes, Distinguished Scientist and Managing Director of Microsoft Research New England
Chayes is well known for her work on phase transitions, which is now giving rise to some of the fastest known algorithms for fundamental problems in combinatorial optimization. She is also one of the world's experts in the modeling and analysis of random, dynamically growing graphs -- which are used to model the Internet, the World Wide Web and a host of other technological and social networks.
Among Chayes' contributions to Microsoft technologies are the development of methods to analyze the structure and behavior of various networks, the design of auction algorithms, and the design and analysis of various business models for the online world.
Sarah Revi Sterling, Director, ICTD Graduate Studies, University of Colorado at Boulder.
Sterling is recognized for conceiving, implementing and leading programs that have had a direct, positive and lasting impact on the lives of women. She pioneered the development of a new participatory community radio technology that enables women to create content for broadcasting from remote locations. She also created and deployed appropriate and sustainable education, health and livelihood programs based upon a variety of innovative networking technologies.
Sarita V. Adve, Professor, Department of Computer Science, University of Illinois at Urbana-Champaign.
Adve has made significant contributions in parallel computing, hardware resiliency, and power management, often by synergistically bringing together hardware- and software-level solutions. She is widely known for her work on hardware and software memory models. These models define the behavior of shared data in parallel hardware and software, and form the foundation for reasoning about parallel programs and optimizing them for performance.
