Contributions to this blog were made by Michael Dunaway from the University of Louisiana at Lafayette and CCC Council Member Daniel Lopresti from Lehigh University.  What if a Category 5 hurricane were heading towards New Orleans right now? What would happen in 2017 that did not happen in 2005? We have learned a great deal from the lessons of Hurricane Katrina and other major incidents, and disaster prevention and recovery has dramatically improved in the last 12 years. Much of the improvement can be attributed to the integration of technology with a “whole of community” approach to emergency management that combines FEMA’s National Incident Management System, with advanced data visualization, […]

The next WATCH talk, called Secure Hardware and Cryptography: Contrasts, Synergies and Challenges is Thursday, May 18th, from 12 PM-1 PM ET. The presenter is Srini Devadas, the Webster Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT). Devadas’s research interests span Computer-Aided Design (CAD), computer security, and computer architecture. He has received the 2014 IEEE Computer Society Technical Achievement award, the 2015 ACM/IEEE Richard Newton technical impact award, and the 2017 IEEE Wallace McDowell award for his research. Devadas is a MacVicar Faculty Fellow and an Everett Moore Baker teaching award recipient, considered MIT’s two highest undergraduate teaching honors. Abstract Numerous cryptographic protocols and mechanisms […]

The following is a guest blog post by CRA Government Affairs Director, Peter Harsha.  As part of its mission to develop a next generation of leaders in the computing research community, the Computing Research Association‘s Computing Community Consortium (CCC) announces the fourth offering of the CCC Leadership in Science Policy Institute (LiSPI), intended to educate computing researchers on how science policy in the U.S. is formulated and how our government works. We seek nominations for participants. LiSPI will be centered around a two-day workshop to be held November 6 – 7, 2017, in Washington, DC. (Full details of LiSPI are available here.) LiSPI will feature presentations and discussions with science policy […]

The National Science Foundation (NSF) has just published the job description for the open Division Director position in the Division of Information and Intelligent Systems (IIS) in the CISE Directorate.  IIS supports the study of the interrelated roles of people, computers, and information. IIS-funded activities 1) develop new knowledge about the role of people in the design and use of information technology; 2) increase our capability to create, manage, and understand data and information in circumstances ranging from personal computers to globally-distributed systems; and 3) advance our understanding of how computational systems can exhibit the hallmark of intelligence. The IIS Division Director has managerial and oversight responsibilities for the division, which comprises […]

Computing Community Consortium (CCC) council member Dr. Jennifer Rexford, Professor and Computer Science Department Chair at Princeton University, has been named the recipient of the 2017 Harrold and Notkin Research and Graduate Mentoring Award. The award, sponsored by the NCWIT Board of Directors, recognizes faculty members from non-profit institutions who distinguish themselves with outstanding research and excellent graduate mentoring, as well as those who recruit, encourage, and promote women and minorities in computing fields. It is bestowed in memory of Mary Jean Harrold and David Notkin, in honor of their outstanding research, graduate mentoring, and diversity contributions. Dr. Rexford spent eight years as a researcher at AT&T Labs Research before […]

The Defense Advanced Research Projects Agency (DARPA) just released a Broad Agency Announcement (BAA) on Lifelong Learning Machines (L2M) with a June 21, 2017, response date. DARPA is soliciting highly innovative research proposals for the development of fundamentally new machine learning approaches that enable systems to learn continually as they operate and apply previous knowledge to novel situations. Current artificial intelligence (AI) systems only compute with what they have been programmed or trained for in advance; they have no ability to learn from data input during execution time, and cannot adapt on-line to changes they encounter in real environments. The goal of the Lifelong Learning Machines (L2M) program is to develop substantially more […]