Foundations of Emerging Technologies (FET)
See program guidelines for contact information.
Foundations of Emerging Technologies (FET) is a new program within CCF that aims to enable radical innovations across all areas traditionally supported by CCF, including the theory, algorithms, software, hardware, and architecture of computing and communication systems, through research at the intersection of computing and biological systems, nanoscale science and engineering, quantum information science, and other nascent, yet promising, areas. Interdisciplinary collaborations between computer and information scientists as well as those in various other fields such as biology, chemistry, engineering, mathematics and physics are highly encouraged, with the aim of pursuing foundational breakthroughs in computer and information science.
The FET program seeks potentially transformative projects in the research areas elaborated below:
Biological Systems Science and Engineering explores opportunities at the intersection of biology and computer science, with a specific focus on activities that advance our understanding of computing and communication processes in biological systems in order to recreate or use them as models for, or demonstrations of, innovative computing and communication systems. Topics of interest include, but are not limited to: understanding the complexity of biological systems via algorithmic, mathematical, and/or stochastic modeling techniques for simulation and analysis of biological systems and biochemical networks at multiple scales; and using the computing power of bio-molecules in designing systems that complement and extend the capability of silicon-based computing systems.
Quantum Information Science explores opportunities in quantum computing, quantum communication, and other quantum-based and related approaches for processing, communicating, and using information. Topics of interest include, but are not limited to: development of a broad and general collection of quantum algorithms (including both algorithm theory and algorithm design); study of quantum programming languages, quantum architectures, and quantum circuits; simulation of quantum algorithms and systems; design of quantum computers and systems; benchmarking, programming, optimizing, and testing quantum computer systems (through, e.g., a cloud service or in the lab); development of both theoretical and practical approaches to fault tolerance; demonstration of scalable quantum computations (paving the road to quantum supremacy, demonstrating quantum supremacy, or post-supremacy); and studies of the use of quantum information in communication and networking, as well as more broadly.
Nanotechnology for Computing and Communication explores opportunities using nanotechnology for (1) disruptive system architectures, circuit micro-architectures, and attendant device and interconnect technology aimed at achieving the highest level of computational energy efficiency for general-purpose computing systems; and (2) architectures and circuits associated with revolutionary device concepts that will greatly extend the practical engineering limits of energy-efficient computation. A cross-layer approach for simultaneous development of hardware design starting at the lowest level of the computing stack and extending to higher levels is encouraged. At the circuits level, alternative state vectors (i.e., non-charge-based devices such as those relying on spin, magnetism, and phase state of materials) possibly involving non-silicon (e.g., carbon nanotubes, two-dimensional materials, optics, etc.) technologies are entertained.
Neuromorphic Computing and Architecture explores opportunities in hardware architectures inspired by the human brain, particularly those enabling synergistic use of materials and device technologies, along with their efficient implementations. Examples include traditional neural network architectures, their recurrent and deep learning versions, other more modern variants (e.g., spiking models), and other computing models of the human brain such as hyper-dimensional computing. Novel algorithms and hardware experimentation of both model-based or model-free machine learning algorithms, e.g., those inspired by information theory and/or statistical mechanics, are entertained as well.
The FET program supports research in information processing and computing with probabilistic devices. Such research should address the future where devices will be plagued by quantum effects, fragility, extreme variability, and low signal-to-noise ratio, thus exhibiting more probabilistic nature of operation than the deterministic systems that exist today.
Funding Opportunities for the Foundations of Emerging Technologies Program: