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DTSTART;TZID=America/New_York:20240415T133000
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UID:43327-1713187800-1713191400@coe.northeastern.edu
SUMMARY:Lin Deng PhD Dissertation Defense
DESCRIPTION:Name:\nLin Deng \nTitle:\nFunction Capacity Expansion of Nano-Optics via Multiplexed Metasurfaces \nDate:\n4/15/2024 \nTime:\n1:30:00 PM \nLocation:\nSL 011 \nCommittee Members:\nProf. Yongmin Liu (advisor)\nProf. Hossein Mosallaei\nProf. Sunil Mittal \nAbstract:\nThroughout history\, the exploration of light has been fundamental to our understanding of the world and has driven advancements in technology and communication. Metasurfaces\, composed of rationally designed nanostructures\, offer a revolutionary means to control light in a prescribed manner. Metasurfaces can operate in conventional free space\, and the emerging integrated photonics domain. Maximizing functionality and degrees of freedom (DOFs) in both arenas is paramount. My thesis aims to push the limit of metasurface capabilities by leveraging multiplexing strategies across input/output parameters such as polarization\, incidence angle\, and waveguide mode. I will present three novel metasurfaces as follows. \n(1) We aim to expand nano-printing multiplexing capacity using the Polarization-Encoded Lenticular Nano-Printing (Pollen) method. When employing three input/output polarization pairs and varying detection angles\, a single metasurface device enables the observation of up to 49 high-resolution nano-printing images. \n(2) By integrating metasurfaces with waveguides\, we can couple guided modes to free space while controlling wavefront and polarization. Our research exploits the multiplexed on-chip metasurface\, which could generate multiple functions depending on the polarization states and waveguide mode propagation directions. \n(3) We investigated mode division multiplexing (MDM) for high-volume optical transmission\, enabling multiple waveguide modes to coexist without interference. By manipulating the orientations of individual nanoantennas\, we have achieved on-demand mode conversion and focusing effects\, demonstrating promising results in various scenarios.  \nIn conclusion\, my research seeks to push the boundaries of metasurface functionalities through innovative multiplexing approaches. The research findings allow us to unlock new possibilities in optical display\, communication\, manipulation\, and beyond by integrating multiple functionalities into single free-space and on-chip metasurfaces.
URL:https://coe.northeastern.edu/event/lin-deng-phd-dissertation-defense/
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CREATED:20240410T205619Z
LAST-MODIFIED:20240410T210310Z
UID:43334-1713189600-1713195000@coe.northeastern.edu
SUMMARY:David Femi Lamptey MS Thesis Defense
DESCRIPTION:Name:\nDavid Femi Lamptey \nTitle:\nCoordinating Camera and Millimeter-Wave Imaging Systems to Detect Concealed Threats in Public Spaces \nDate:\n4/15/2024 \nTime:\n2:00:00 PM \nLocation:\nSnell Library CoLab J \nCommittee Members:\nProf. Carey Rappaport (Advisor)\nProf. Octavia Camps\nProf. Sarah Ostadabbas \nAbstract:\nThis paper tackles the problem of uniquely identifying and tracking targets for the purposes of concealed threat detection in public spaces. Cameras\, computer vision techniques\, and deep neural networks have made the task of detecting and tracking people in videos almost trivial but provide no means for the detection of otherwise concealed threats a target may be carrying\, while millimeter-wave radars provide a means to perform accurate scanning for concealed objects on a target\, but do not provide enough information for tracking and unique identification of a target\, particularly one with a concealed threat or contraband. This paper proposes a method utilizing a video camera stream and millimeter-wave multi-beam radar fusion in order to identify people in a public space\, track them\, and identify the best beam in a multi-beam radar to refer to at any given point in time in order to obtain the best scan of a particular target from the millimeter-wave radar\, which will then enable an effective determination of a concealed threat. We focus on the computer vision aspects of this challenge\, implementing a tracker and an algorithm to look up the best beam in the radar to associate with a target at a point in time. This algorithm uses the properties of the camera\, such as the video resolution\, field of view of the camera\, internal parameters of the camera\, and elevation of the camera\, in order to perform an estimation of the distance of a person from the camera and perform a determination of the optimal beam to look at for a clear view of the target. This approach was optimized using an efficient spatial indexing lookup technique based on the R-tree data structure. The results from this paper show that this technique is robust\, accurate\, and versatile for a wide variety of scenarios and that the real-time tracking and association between targets and millimeter-wave beams can be performed accurately. We conclude that this technique is a fitting solution to the problem of camera and millimeter-wave multi-beam radar fusion in order to identify concealed threats on targets in public spaces.
URL:https://coe.northeastern.edu/event/david-femi-lamptey-ms-thesis-defense/
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