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About me



  • 2023 - Present
    SUNY Research Foundation, University at Buffalo

    Research Assistant

    • Developing a deep CNN model for 3D reconstruction of endoscopic images using estimated pose and depth scene
    • Training and testing of model on EndoSLAM dataset consisting of images with 6D ground truth pose of various types of
    endoscope cameras
    • Improving accuracy and efficiency of endoscopic procedures by providing a more detailed 3D reconstruction of the scene for
    medical professionals to analyze and make informed decisions

  • 2021 - 2022
    ACPS Research Group, University of Agder (UiA)

    Visiting Masters Student

    • Modeled a multi-agent DDPG system to coordinate and control fleet of drones to cover an area of interest while minimizing
    intersection area (Masters’ Thesis)
    • Launched the multi-agent system in the AirSim environment and formulated a custom error metric to evaluate the system,
    resulting in a coverage of 60%
    • Built CNN model to categorize 17 different classes of drones based on RF signals from transmitters and attained 99.09%
    accuracy outperforming existing state-of-the-art models (Publication)
    • Executed a lightweight CNN model on Nvidia Jetson AGX and classified different classes of background noise present in
    the human speech signals and accomplished 95.2% accuracy (Publication)
    • Compiled a comprehensive repository of mmWave radar and visual imagery database for 6 different drone models