The Foundations of Emerging Technologies (FET) program supports overarching fundamental research in disruptive technologies and models in computing and communication. Current exemplars include but are not limited to biological computation, nanoscale science and engineering, quantum information science and engineering, neuromorphic computing, and other disruptive technologies and computing models.
The goal of the FET program is to germinate and foster radical innovations in computing and communication modalities, in topics spanning the various fields of research traditionally funded by the core CCF programs, which may include the theory, algorithms, software, hardware, and architecture of computing and communication systems, as applied to these innovations. Interdisciplinary collaboration between computer and information scientists as well as those in various other fields such as biology, chemistry, engineering, mathematics, and physics are highly encouraged to promote groundbreaking inventions and paradigm-shifting solutions for hardware and software platforms in computing and communication.
The FET program seeks transformative research projects in any disruptive area aligned with the goals of the program as identified above. The following research areas are called out specifically at this time.
The Biological Systems Science and Engineering program element explores opportunities at the intersection of biology and computer science, with a specific focus on activities that advance understanding of computing and communication processes in biological systems 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 harnessing the computing power of biomolecules in designing systems that complement and extend the capability of silicon-based computing systems. Research in the Synthetic Biology area, with a focus on constructing/redesigning novel hybrid programmable biological systems capable of computing and information processing, is also in scope for the program. Some examples for research topics include but are not limited to issues in resource allocation in a designed synthetic cell/system, design tools for engineering biological systems, and advanced biomolecule-based data-storage devices.
The Quantum Information Science program element explores new research ideas in quantum computing, quantum communication, and other quantum-based approaches for processing, exchanging, and using information. Topics of interest include but are not limited to the design, development, and rigorous analysis of a broad and general collection of quantum; 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 experimentally; development of both theoretical and practical approaches to fault tolerance; demonstration of scalable quantum computations, thereby paving the road to quantum supremacy; and explorations into quantum information in communication and networking.
Additionally, the FET program promotes research that demonstrates how computational and engineering principles can be synergistically advanced to mimic brain-like problem solving with novel neural and cognitive architectures. In particular, the program encourages research on neuromorphic computing with hardware-friendly learning mechanisms such as spike-timing dependent plasticity (STDP), reinforcement and Q-learning. Proposals on brain-computer interfaces will be considered by the FET program if they aim at solving problems in fundamentally new ways.
The FET program also solicits research on emerging topics of quantum-like, but non-qubit-based, computing paradigms. Such methodologies may typically address hard computational problems in integer factorization, hardware methods to solving NP-hard problems, machine learning, and so on. Examples of such efforts may include but are not limited to computing using probabilistic bits and single-flux quantum logic circuits.
The FET program promotes innovative research on multiscale modeling of computing and communications systems based on future emerging technologies as well.