The workshop was 1.5 days in the Washington, DC area. It was an opportunity for attendees to meet National Science Foundation program officers as well as representatives from other agencies. The content covered at the workshop came from the 2017 CCC Symposium, recent CCC visioning workshops, and CRA programs for Career Mentoring and Leadership in Science Policy.
The Cybersecurity Taskforce of the CCC will hold a leadership workshop to envision the future of embedded security research and education from hardware to cyberphysical systems to human factors.
While it has been known for some time that quantum computers could in principle solve problems that are intractable on today’s supercomputers such as breaking public key cryptography and solving hard computational chemistry problems, the field of quantum computing is still at an early stage. Recent progress in realizing small scale quantum computers is encouraging and these devices may scale up further in the near future. However, currently, only very few opportunities exist to bring quantum computing experts together with experts from other computer science fields with much to offer: programming languages, compiler design, computer architecture, and design automation in an exchange of ideas.
The Robotic Materials workshop showcased some of the ongoing interdisciplinary work at the intersection of computing, robotics, and material science.
In this cross-disciplinary workshop, we will bring together leading researchers in computing, health informatics, and behavioral medicine to develop an integrative research agenda regarding sociotechnical interventions to reduce health disparities and improve the health of socio-economically disadvantaged populations. As part of these discussions, approaches for guarding against unintended consequences of general interventions will also be explored. To do so, this workshop will focus on integrating insights and findings from each of these fields, identifying gaps in understanding between fields, and surfacing opportunities for future interdisciplinary research to address relevant challenges.
This workshop aims to identify key challenges and open questions that currently limit both our theoretical understanding of fairness and machine learning, and their applicability in practice.
The historical increases in computing performance and reductions in power consumption, size, weight and cost of computing devices are ingrained in the fabric of the research community. These improvements have fueled innovation across scientific domains, health, industry, and government. But clock speeds have been relatively flat for over a decade and current transistor scaling will be reaching limits that are both technological and economic over the next decade. While alternative models of computation are being explored, including quantum and neuro-inspired, digital computing will remain the dominant computational technology for the foreseeable future.