We present a method for decentralized, multi-robot exploration in adverse environments where communication is minimal. A key conceptual feature of our method is enabling implicit coordination between robots by training a Convolutional Neural Network (CNN) as a heuristic for planning using Monte Carlo Tree Search (MCTS). Our method consists of...
The dissertation focuses on the engineering of light-matter interaction using plasmonic nanoparticles and metamaterials to achieve enhanced luminescence and based on which to improve the performance of biosensing and light-emitting technologies. We designed and fabricated a spectrum of nanostructures to exhibit particular dispersion relations capable of controlling the spontaneous emission...
The effect of cosputtered catalyst on growth and alignment of carbon nanotubes (CNTs) grown by plasma enhanced chemical vapor deposition (PECVD) was investigated. Aligned CNTs were observed using a cosputtered catalytic metal deposited directly on boro-aluminosilicate glass. Catalytic metal alloys were sputtered directly onto the substrate using magnetron sputtering. Deposition...
With the rapid growth of worldwide internet traffic in data centers and clouds, silicon photonics has been utilized to provide enormous data bandwidth and outstanding energy efficiency over electronics. Computing servers and storage servers that are connected by communication links are relying more on optical rather than electrical means mainly...
In this dissertation, a series of studies in the field of terahertz (THz) science are presented, specifically using nonlinear THz spectroscopy. We exploit huge field enhancement and subwavelength confinement in plasmonic structures. There are three distinct projects which will be discussed: nonlinear THz spectroscopy using plasmonic induced transparency (PIT), THz-triggered...
This dissertation addresses few-shot object segmentation in images. The goal of segmentation is to label every image pixel with a class of the object occupying that pixel, where the class may represent a semantic object category or instance. In few-shot segmentation, training and test datasets have different classes. Every new...