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 $375,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support a collaborative research effort to accelerate the design and development of engineered photonic materials using a data-driven deep learning approach. The project aims to establish deep learning frameworks to construct photonic metamaterials with tailored optical properties, integrate information on constituent material platforms into deep...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $467,930 to Northeastern University to design and implement a novel class of metasurface-based optical neural networks, termed "meta-ONNs". The goal is to develop multiplexed meta-ONNs that can operate at optical frequencies and perform diverse functions like all-optical image recognition and pattern generation. The project consists of three main research thrusts: (1)...
This National Science Foundation Project Grant of $1,198,092 will support research at Northwestern University from August 1, 2022 to July 31, 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). The university will design photonic lattices and multilayer structures that can confine light in small spaces near metal nanostructures and support electrically-driven excitation. Researchers will fabricate new architectures based on multilayer nanoparticle arrays and realize...
The National Science Foundation (NSF) awarded a $600,000 project grant under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the Regents of the University of Michigan to support research on reinforcement learning and transformer-inspired approaches for smart photonics inverse design. The project aims to enable non-experts to use artificial intelligence models to design sophisticated photonic structures for optical applications, while also advancing...
This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $500,000.00 over a 4-year period to Purdue University to develop a novel hybrid thin film platform with unique optical properties for photonic integrated circuits (PICs). The research aims to advance understanding of electro-optical and magneto-optical coupling effects in complex nanoscale hybrid metamaterials, and demonstrate key building blocks for future large-scale PICs including...
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 $440,000 federal Project Grant award, provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program, supports collaborative research at Northeastern University on "deep learning guided twistronics for self-assembled quantum optoelectronics". The key objectives are to use computer-aided deep learning models and theoretical tools to predict and guide the synthesis of novel "twistronic" materials composed of stacked...
This $380,000 Project Grant award from the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems under CFDA Program 47.041 (Engineering) will fund the development of new types of on-chip "topological photodetectors" that can detect and differentiate between different modes and properties of light, such as its phase, polarization, and orbital angular momentum. These novel photodetectors, based on emerging quantum materials like Weyl semimetals,...
This $500,000 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research at the University of Maryland, College Park on integrated photonic circuits for next-generation communications and computing. The project explores the use of phase change materials to dynamically reconfigure the transverse modes in multimode waveguides, creating "synthetic modal dimensions" for novel optical information processing. Key research objectives...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program provides $750,000 to Northeastern University to develop innovative engineered photonic materials using a data-driven deep learning approach. The research aims to accelerate the discovery, design, and implementation of new photonic metamaterials with tailored optical properties for applications in areas such as lasers, optical communications, quantum computing, and solar energy harvesting. The 3-year project will establish deep learning frameworks to construct photonic metamaterials, integrate information on optical properties of constituent materials, and investigate hybrid material systems coupling photonic structures with quantum emitters and nonlinearities. The interdisciplinary effort combines materials science, photonics, engineering, and artificial intelligence to create a comprehensive library of meta-atoms and meta-molecules and their optical responses, ultimately driving transformative applications of photonic metamaterials.