The following blog was first posted on the CRA Bulletin.  After nearly 20 years at the helm of the Computing Research Association, Executive Director Andrew Bernat has retired from his position, marking the close of his incredible career that has spanned more than 40 years. Over the course of his career, he was founding member and chair of the Computer Science Department at the University of Texas at El Paso, a NSF Program Director and finally executive director of CRA since 2002. Under his leadership the association has seen a dramatic, positive transformation, more than tripling in size and launching significant new efforts in research visioning, widening participation, and postgraduate […]

The Climate Change AI (CCAI) organization, which is composed of volunteers from academia and industry who believe that tackling climate change requires concerted societal action in machine learning, has announced a new Call for Proposals: Climate Change AI Innovation Grants.  Artificial Intelligence (AI) and machine learning (ML) can help support climate change mitigation and adaptation, as well as climate science, across many different areas, for example energy, agriculture, forestry, climate modeling, and disaster response (for a broader overview of the space, please refer to Climate Change AI’s interactive topic summaries and materials from previous events). However, impactful research and deployment have often been held back by a lack of data […]

The CRA-Industry Committee invites you to attend the Virtual Roundtable on Best Practices on using the Cloud for Computing Research on September 15, 2021, from 3:00 PM – 4:15 PM Eastern Daylight Time. A major focus in computing research across industry, academia, and government is to advance the frontiers of computing by experimenting with leading-edge compute platforms.  This was initially at odds with early instances of cloud/warehouse computing that focused on deploying commodity rather than state-of-the-art systems.  However, cloud computing platforms have advanced significantly during the last two decades to the point where there are now many notable examples of their use in research.  Further, the cloud’s “pay as you go” […]

John A. Stankovic, University of Virginia, will present “Towards Ambient Intelligence in Smart Healthcare,” part of the National Science Foundation (NSF) Computer & Information Science & Engineering (CISE) Distinguished Lecture Series on September 30th, 2021, from 11:00 AM to 12:15 PM ET. Professor John A. Stankovic is the BP America Professor in the Computer Science Department at the University of Virginia and Director of the Link Lab. He is a Fellow of both the IEEE and the ACM. He has been awarded an Honorary Doctorate from the University of York, U.K., for his work on real-time systems. He won the IEEE Real-Time Systems Technical Committee’s Award for Outstanding Technical Contributions and Leadership.  He also received […]

In July, the White House Office of Science and Technology Policy and the National Science Foundation released a Request For Information (RFI) to gather public input on the National AI Research Resource (NAIRR) implementation plan. The deadline has been extended, to October 1st, to hopefully elicit more diverse responses. “Given that we want to hear from as many folks as possible — we’d really like a broad and diverse set of perspectives among the responses — we felt it best to extend the RFI response date by a month,” Erwin Gianchandani, who co-chairs the task force as NSF’s representative, told FedScoop in an article. “We believe that timeline will maximize responses while still allowing us to […]

The National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Directorate has some upcoming solicitation deadlines. Check them out! Center for Advancement and Synthesis of Open Environmental Data and Sciences Full Proposal Deadline Date: September 15, 2021 NSF seeks to establish a Center fueled by open and freely available biological and other environmental data to catalyze novel scientific questions in environmental biology through the use of data-intensive approaches, team science and research networks, and training in the accession, management, analysis, visualization, and synthesis of large data sets. The Center will provide a vision for speeding discovery through the increased use of large, publicly accessible datasets to address biological research questions through collaborations […]