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Integrated metasystem for Fourier optics, machine learning and imaging
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主讲人: Tingyi Gu (University of Delaware)
地点: 腾讯会议 ID:468 960 635
时间: 2021年11月3日 (星期三) 12:00-14:00
主持 联系人: 胡小永 (Tel: 62768705)
主讲人简介: Tingyi Gu’s research focuses on integrated photonic devices, developing optical components with new materials for optical communication and sensing applications. She investigates the physics of silicon and chalcogenide-based hybrid nanophotonic devices, and characterizes their potential for large-scale integration, high speed on-chip signal processing and sensing applications. Her work studies nonconventional photonic and electronic properties of nanostructured materials built by different integration techniques and aims to achieve a good understanding of the nanostructured materials photonic functionalities and build a scalable integrated photonic system. She joined the ECE faculty of the University of Delaware in the fall of 2016. She received a B.S. with honors in electrical engineering from Shanghai Jiao Tong University, and M.S. and Ph.D. degrees in electrical engineering from Columbia University. For her Ph.D., she worked on silicon based nanophotonic and optoelectronic devices. She has held positions at the Center for High Technology Materials in the University of New Mexico, Zhejiang University in China, Alcatel-Lucent Bell Labs, and Princeton University in NJ. At Bell labs, she worked on silicon photonic network-on-chip systems. She completed postdoctoral research in the Large-Scale Integrated Photonics research group at Hewlett Packard Labs in Palo Alto, CA, studying large-scale nonlinear photonic circuits. She also completed postdoctoral work with Prof. Craig B. Arnold at Princeton University, studying solution processed chalcogenide materials.

The advancement of nanotechnologies enables powerful control of photons by subwavelength structures. In recent years, rapid advancement ofmetasurfaceand metamaterials reveal the potential ofnanophotonicsin the applications across disciplines, from hyperspectral imaging to mathematical operations. One question emerges as: ismetasurfaces’ applications limited in deterministic spatial/spectral information or it can play more powerful roles in machine learning and dealing with uncertainties. In this talk I will review recent works on this track and introduce integrated photonicmetasurfacesystems. With lithographically defined inter-layer alignment, we demonstrate diffractive deep optical network on silicon photonic platform, towards broadband spatial pattern classification and hyperspectral imaging. The high-throughput vector-by-matrix multiplications is enabled by 103passive subwavelength phase shifters as weight elements. The integrated metasystem perform analogue optical computing tasks, from simplefouriertransformation to complicated image classification. In the presentation, we will illustrate the design principle of the foundry compatible metasystem, and its implementation of basic low loss photonic mode converters, differentiators, and image classifiers.