Andrea Alù, PhD
City University of New York
Biography:
Andrea Alù is a Distinguished Professor at the City University of New York (CUNY), the Founding Director of the Photonics Initiative at the CUNY Advanced Science Research Center, and the Einstein Professor of Physics at the CUNY Graduate Center. He received his Laurea (2001) and PhD (2007) from the University of Roma Tre, Italy, and, after a postdoc at the University of Pennsylvania, he joined the faculty of the University of Texas at Austin in 2009, where he was the Temple Foundation Endowed Professor until Jan. 2018. Dr. Alù is a Fellow of the National Academy of Inventors (NAI), the American Association for the Advancement of Science (AAAS), the Institute of Electrical and Electronic Engineers (IEEE), the Materials Research Society (MRS), Optica, the International Society for Optics and Photonics (SPIE) and the American Physical Society (APS). He is a Highly Cited Researcher since 2017, a Simons Investigator in Physics, the director of the Simons Collaboration on Extreme Wave Phenomena Based on Symmetries, and the Editor in Chief of Optical Materials Express. He has received several scientific awards, including the NSF Alan T. Waterman award, the Blavatnik National Award for Physical Sciences and Engineering, the IEEE Kiyo Tomiyasu Award, the ICO Prize in Optics, the Optica Max Born Award, and the URSI Issac Koga Gold Medal.
Abstract:
The rapid growth of data-intensive applications has exposed fundamental limits in conventional electronic computing architectures, particularly in terms of speed, energy efficiency and parallelism. Our recent efforts have been exploring an alternative paradigm: computing at the speed of light using engineered metasurfaces. Metasurfaces—ultra-thin, subwavelength-structured materials—enable precise control over the amplitude, phase, and polarization of electromagnetic waves. By leveraging these capabilities, we have been demonstrating how complex mathematical operations can be encoded directly into the physical interaction between light and matter, effectively performing computation with light waves. Our approach relies on designing metasurfaces whose complex optical response implements specific linear and nonlinear transformations. By mapping computational problems—such as differentiation, convolution, and matrix multiplication—onto wavefront manipulations, the metasurface acts as an analog processor that transforms input optical fields into computed outputs in real time. Unlike digital processors, which execute operations sequentially and are constrained by clock speeds, metasurface-based systems exploit the inherent parallelism of light propagation, enabling ultrafast, energy-efficient processing with minimal latency. Using nanofabricated metasurfaces operating across a wide range of wavelengths, we implement key computational primitives and evaluate their performance in terms of accuracy, bandwidth and scalability. Our results highlight the robustness of light-based computing against fabrication imperfections and input noise, while also underscoring its compatibility with integrated photonic platforms. Beyond proof-of-concept demonstrations, this work outlines a pathway toward practical optical computing systems. In particular, metasurface analog computing offers a promising route for low-power, high-throughput inference tasks, where approximate solutions are sufficient and latency is critical. Overall, our work establishes metasurfaces as a powerful platform for computing at the speed of light, bridging nanophotonics and information processing. By harnessing the physics of wave-matter interactions, this approach opens new opportunities for rethinking computation beyond traditional electronic limits, paving the way for next-generation hybrid optical–electronic systems.
Andrea Alù is a Distinguished Professor at the City University of New York (CUNY), the Founding Director of the Photonics Initiative at the CUNY Advanced Science Research Center, and the Einstein Professor of Physics at the CUNY Graduate Center. He received his Laurea (2001) and PhD (2007) from the University of Roma Tre, Italy, and, after a postdoc at the University of Pennsylvania, he joined the faculty of the University of Texas at Austin in 2009, where he was the Temple Foundation Endowed Professor until Jan. 2018. Dr. Alù is a Fellow of the National Academy of Inventors (NAI), the American Association for the Advancement of Science (AAAS), the Institute of Electrical and Electronic Engineers (IEEE), the Materials Research Society (MRS), Optica, the International Society for Optics and Photonics (SPIE) and the American Physical Society (APS). He is a Highly Cited Researcher since 2017, a Simons Investigator in Physics, the director of the Simons Collaboration on Extreme Wave Phenomena Based on Symmetries, and the Editor in Chief of Optical Materials Express. He has received several scientific awards, including the NSF Alan T. Waterman award, the Blavatnik National Award for Physical Sciences and Engineering, the IEEE Kiyo Tomiyasu Award, the ICO Prize in Optics, the Optica Max Born Award, and the URSI Issac Koga Gold Medal.
Abstract:
The rapid growth of data-intensive applications has exposed fundamental limits in conventional electronic computing architectures, particularly in terms of speed, energy efficiency and parallelism. Our recent efforts have been exploring an alternative paradigm: computing at the speed of light using engineered metasurfaces. Metasurfaces—ultra-thin, subwavelength-structured materials—enable precise control over the amplitude, phase, and polarization of electromagnetic waves. By leveraging these capabilities, we have been demonstrating how complex mathematical operations can be encoded directly into the physical interaction between light and matter, effectively performing computation with light waves. Our approach relies on designing metasurfaces whose complex optical response implements specific linear and nonlinear transformations. By mapping computational problems—such as differentiation, convolution, and matrix multiplication—onto wavefront manipulations, the metasurface acts as an analog processor that transforms input optical fields into computed outputs in real time. Unlike digital processors, which execute operations sequentially and are constrained by clock speeds, metasurface-based systems exploit the inherent parallelism of light propagation, enabling ultrafast, energy-efficient processing with minimal latency. Using nanofabricated metasurfaces operating across a wide range of wavelengths, we implement key computational primitives and evaluate their performance in terms of accuracy, bandwidth and scalability. Our results highlight the robustness of light-based computing against fabrication imperfections and input noise, while also underscoring its compatibility with integrated photonic platforms. Beyond proof-of-concept demonstrations, this work outlines a pathway toward practical optical computing systems. In particular, metasurface analog computing offers a promising route for low-power, high-throughput inference tasks, where approximate solutions are sufficient and latency is critical. Overall, our work establishes metasurfaces as a powerful platform for computing at the speed of light, bridging nanophotonics and information processing. By harnessing the physics of wave-matter interactions, this approach opens new opportunities for rethinking computation beyond traditional electronic limits, paving the way for next-generation hybrid optical–electronic systems.
