This $199,040 Project Grant, awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop new classes of computational algorithms that combine the benefits of direct computer simulations and the speed of machine learning predictions. The project, titled "XTRIPODS: HYBRID SCIENCE-MACHINE LEARNING SOLVERS FOR NANOPHOTONICS AND METAMATERIALS," will embed scientific knowledge into the machine learning...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $596,121 to the Trustees of Dartmouth College to investigate how light-sensitive molecular additives, called switchable molecules, can control the color reflected from liquid crystal surfaces. The research aims to gain insights into leveraging this capability to develop low-energy devices and applications such as smart price tags, anti-counterfeit...
This $296,555 Project Grant from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support the development of reduced basis enhancements for neural networks and their application to quantum materials simulation. Specifically, the University of Massachusetts Dartmouth will combine traditional reduced basis methods with deep learning techniques to build an analysis-driven computational emulator for parameterized partial differential equations....
This $350,000 federal Project Grant was awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program. The goal of the research is to develop accurate mathematical models and computer simulations for studying non-equilibrium systems with memory effects, such as those found in biosystems, plasma evolution, and solid-state nanostructures. The Principal Investigator will focus on analytical and numerical approaches to statistical transport...
This Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $269,343 to the University of California, San Diego for research exploring geometric approaches to physical simulations. The award aims to develop new computational methods using non-Euclidean geometry to more accurately simulate turbulent fluids and solve partial differential equations on infinite...
This five-year Project Grant from the National Science Foundation's Division of Information and Intelligent Systems and Computer and Information Science and Engineering program (CFDA 47.070) provides $330,293 to Texas A&M Engineering Experiment Station (doing business as Tees) to develop novel methods for sparse sampling and reconstruction in computer graphics rendering. The award seeks to dramatically reduce the number of photons required to generate high-quality images through importance...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $450,000 to Colorado State University (CSU) from August 1, 2024 to July 31, 2027. The project aims to develop a novel adaptive, fully anisotropic multiscale hp-element method to revolutionize simulation-based design in computational electromagnetics (CEM). The research will create exponentially convergent techniques to accurately and efficiently model multiscale, non-smooth behavior...
This $375,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) aims to accelerate the discovery, design, and implementation of new engineered photonic materials, particularly photonic metamaterials, through a data-driven deep learning approach. The project, led by the Georgia Tech Research Corporation, will establish deep learning frameworks to construct photonic metamaterials, integrate information on tailorable optical...
This $417,766 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program supports the development of a computational framework for replicating, designing, and rapidly prototyping nano-structural coloration architectures. The goal is to enable digital twinning of nature-inspired structural coloration through efficient computer simulations, allowing the fabrication of novel optical materials with...
This $800,000 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program supports the development of innovative snapshot computational imaging systems that leverage metaoptics technology. The project, led by Dartmouth College, aims to create computational camera simulators capable of modeling the complex interactions of light across various dimensions, and to leverage these tools to design and build...
This Project Grant award for $490,402 was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program. The award, granted to Trustees of Dartmouth College, will develop new methods to model and simulate the interaction of light with materials that have both well-defined surfaces and volumetric properties, across different scales. This will enable accurate visualizations and simulations of complex materials in applications like computer graphics, remote sensing, medical imaging, and nuclear engineering. The project aims to create a unified approach to representing shape and appearance, using Gaussian processes to describe material geometry and determine which features should be considered part of the main shape versus finer-scale variations. The research outcomes are expected to have broad impact in disciplines that require simulating the transport of neutral particles in correlated disorder across arbitrary scales. The project period runs from July 1, 2025 to June 30, 2028.