Today marks the end of the following Computing Community Consortium (CCC) Council member’s time on the Council. We would like to highlight them once again and thank them for their exceptional dedication and service to the CCC and to the broader computing research community. Mark D. Hill, Microsoft and University of Wisconsin, Madison Mark joined the Council in 2013 and was Chair from 2018-2020. During his tenure as Chair, he spearheaded CIFellows 2020, the 2019 AI Roadmap, and two visioning workshops on Identifying Research Challenges in Post Quantum Cryptography Migration and Cryptographic Agility and Wide-Area Data Analytics. David Parkes, Harvard University David joined the Council in 2018 and organized the […]

The Computing Community Consortium (CCC), along with Code 8.7, is pleased to announce the release of the CCC / Code 8.7 Applying AI in the Fight Against Modern Slavery Workshop Report. This March 2020 workshop brought together over 50 members of the computing research community along with anti-slavery practitioners and survivors to lay out a research roadmap aimed at applying AI to the fight against human trafficking.  The primary goal was to explore ways in which long-range research in artificial intelligence (AI) could be applied to the fight against human trafficking. Building on the kickoff Code 8.7 conference held at the headquarters of the United Nations in February 2019, the […]

The National Science Foundation (NSF) and the White House Office of Science and Technology Policy announced the government, academic, and private sector representatives who will serve on the National Artificial Intelligence Research Resource Task Force as directed by Congress in the “National AI Initiative Act of 2020.” The Computing Community Consortium (CCC) and its parent organization the Computing Research Association (CRA) provided significant input to policymakers drafting provisions for the National AI Initiative Act of 2020. In 2018-2019, the CCC brought together over 100 members of the research community, led by Yolanda Gil (University of Southern California) and Bart Selman (Cornell University) to come up with a research roadmap for AI. Fei Fei Li (Stanford University), […]

Minka Stoyanova began her CIFellowship in January 2021 after receiving her PhD from City University of Hong Kong in October 2019. Stoyanova is at University of Colorado Boulder working with Reece Auguiste, Associate Professor of Media, Communication and Information at UC Boulder.  Current Project My current research project is focused on how digital information technologies can be used to create embodied and affective experiences in urban environments. Specifically, the project is aimed at using mobile phone augmented reality technology and digital storytelling methods to situate historic and community narratives within urban environments. Historic material held in museums and archives often becomes detached from the communities and the locations it represents. […]

The Association for Computing Machinery (ACM) and IEEE Computer Society recently announced that former Computing Research Association (CRA) and Computing Research Association- Widening Participation (CRA-WP) Board Member and current National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Assistant Director Margaret Martonosi is the recipient of the 2021 Eckert-Mauchly Award. Martonosi is the Hugh Trumbull Adams ’35 Professor of Computer Science at Princeton University, where she has been on the faculty since 1994. In 2018, she led the Computing Community Consortium (CCC) effort to understand the next steps in Quantum Computing for computer science. The Eckert-Mauchly Award is known as the computer architecture community’s most prestigious award. Martonosi was cited […]

Rika Antonova began her CIFellowship in January 2021 after receiving her PhD from KTH Royal Institute of Technology in Stockholm in December 2020. Antonova is at Stanford University working with Jeannette Bohg, Assistant Professor of Robotics at Stanford.  Current Project Machine learning is transforming robotics: we can now solve high-dimensional problems that have been intractable before, if given large amounts of data and ample training time. However, to go beyond structured factory settings, it is important for robots to adapt to changes in the environment/task without lengthy re-training and data collection. A related problem is closing the simulation-to-reality gap: adapting to the real world after training in simulation. My goal […]