ACM SIGMETRICS 2018
Irvine, California, USA
June 18-22, 2018
Jon Kleinberg is the Tisch University Professor in the Departments of Computer Science and Information Science at Cornell University. His research focuses on issues at the interface of algorithms, networks, and information, with an emphasis on the social and information networks that underpin the Web and other on-line media. He is a member of the National Academy of Sciences, the National Academy of Engineering, and the American Academy of Arts and Sciences; and he is the recipient of research fellowships from the MacArthur, Packard, Simons, and Sloan Foundations, as well as awards including the Harvey, Lanchester, and Nevanlinna Prizes, the Newell Award, and the ACM Prize in Computing.
Margaret Martonosi is the Hugh Trumbull Adams '35 Professor of Computer Science at Princeton University, where she has been on the faculty since 1994. She is also currently serving a four-year term as Director of the Keller Center for Innovation in Engineering Education. Martonosi holds affiliated faculty appointments in Princeton EE, the Center for Information Technology Policy (CITP), the Andlinger Center for Energy and the Environement, and the Princeton Environmental Institute. She also holds an affiliated faculty appointment in Princeton EE. From 2005-2007, she served as Associate Dean for Academic Affairs for the Princeton University School of Engineering and Applied Science. In 2011, she served as Acting Director of Princeton's Center for Information Technology Policy (CITP). From August 2015 through March, 2017, she served as a Jefferson Science Fellow within the U.S. Department of State. Martonosi's research interests are in computer architecture and mobile computing, with particular focus on power-efficient systems. Her work has included the development of the Wattch power modeling tool and the Princeton ZebraNet mobile sensor network project for the design and real-world deployment of zebra tracking collars in Kenya. Her current research focuses on hardware-software interface approaches to manage heterogeneous parallelism and power-performance tradeoffs in systems ranging from smartphones to chip multiprocessors to large-scale data centers.