Algorithms which are efficient and robust are essential to meet the increasing computational demands in the world today. In this thesis, we consider the analysis and design of both distributed algorithms for dynamic average consensus and centralized algorithms for convex optimization.
Dynamic average consensus consists of a group of agents,...
Every object emits radiation depending of their temperature. Objects between 300K to 100K emit radiation in the infrared range (1-12µm). These radiations cannot be seen by the human eyes. Infrared detectors find applications in many aspects of life, from night vision and target tracking for homeland security and defense, to...
A core problem in many computer vision applications is visual recognition (including object classification, detection and localization). Recent advances in artificial neural networks (aka ”deep learning”) have significantly pushed forward the state-of-the-art visual recognition performances. However, due to the lack of semantic structure modeling, most current deep learning approaches do...
Hybrid pixel detectors, comprising of pixelated sensors coupled to readout integrated circuits (ROICs) with complex in-pixel processing, are essential for many of today’s scientific instruments and imaging systems. Large-area detectors are required in a variety of systems: from detectors for synchrotron beamlines to telescopes for astronomy, which range from a...
Power and energy are becoming the limiting factors for computer designs and systems, and energy efficient functional units are getting more popular in such systems. Some of the design methodologies that are getting more common include voltage overscaling and employing imprecise instructions. These functional units need to be characterized correctly...
Quantum technologies have the capability of greatly increasing the security of communication systems. Many components are required for a full quantum network including memory, repeaters, routers, and detectors. The efficiencies of quantum communication technologies suffer greatly due to their inherent sensitivity to loss. Low-loss propagation and high detection efficiency can...
Abstract The work presented in this dissertation addresses three broad areas of video signal processing: video transmission, motion estimation and error concealment. In the first category, focused on the source-side, we present two machine learning models for efficient content-aware resource allocation and packet prioritization for video transmission over shared/constrained, lossy...
The rapid development of flexible electronics enables a huge amount of bio-integrated applications with advantages of the mechanical compliance, stretchability and comformability of the devices. My dissertation further advances this area by a series of projects, which include designing and optimizing novel compliant structures, proposing novel elastomer encapsulation process for...
In this thesis, the optical gain mechanism in low-light conditions of phototransistor detectors (PTDs) is explored. An analytical formula is derived for the physical limit on the minimum number of detectable photons for PTDs. This formulation shows that the sensitivity of the PTD, regardless of its material composition, is related...
The surge in smart phones, connected vehicles, and Internet-of-Things (IoT) has exponentially increased mobile data usage. While adding new spectrum is the most straightforward way to to meet the skyrocketing demands, the scarcity of spectrum resources and high cost for clearing spectrum make it the most expensive way. This has...
Mid-infrared lasers, emitting in the spectral region of 3-12 µm that contain strong characteristic vibrational transitions of many important molecules and two atmospheric transmission windows, are highly desirable for spectroscopy sensing, infrared countermeasures, and free space communications. Previously, single-element quantum cascade lasers (QCLs) have been demonstrated with up to watt-level...
Location awareness will be crucial for many future wireless network applications, such as the Internet of Things (IoT) and vehicular networks. In particular, the IoT will connect a massive number of new devices to wireless networks. Localization solutions that work in urban environments and have solutions which scale well with...
We start from a set of users communicating over a Gaussian multiple access wire-tap channel with confidential messages, where users attempt to transmit private messages to a legitimate receiver in the presence of an eavesdropper. While prior work focused on the case where the users were cooperative, we assume that...
Demand Response (DR) is an approach that allows electricity users to actively participate in keeping supply-demand balance in power systems, or its future version, smart grid, in order to increase the system efficiency, lower consumers' electricity bills, and thus improve social welfare. To encourage users' participation in DR, a time-varying...
With the growing size of networks and datasets and the lack of centralized access to information, distributed control and optimization become inevitable. In the first part of this thesis, we develop an asynchronous Newton-based distributed optimization algorithm and analyze its convergence properties. Our algorithm benefits from the fast convergence properties...
Low-dimensional materials have emerged as a promising platform for ultrathin electronic and optoelectronic devices. The span of electronic properties covers the spectrum from metallic through small and medium bandgap semiconductors to large bandgap insulators, providing all the necessary components to fabricate a variety of devices. Compared to bulk-semiconductor based devices,...
Super-resolution (SR) has become one of the most critical problems in image and video processing. In Chapter 2 of this thesis, a detailed review of existing Deep Learning (DL) techniques for addressing the SR task, with an emphasis on how DL and analytical techniques can be combined, is provided. Chapter...
The commercial success of personal computing has led to the rapid creation and proliferation of diverse electronic systems including desktops, laptops, tablets, mobile devices, and embedded systems. For the past five decades, silicon has served as the base material for computing electronics. However, with increasing demand for unconventional electronics (e.g.,...
Convolutional neural networks have become a staple in computer vision and image processing tasks. The capacity for these networks to perform visual pattern recognition in a data-driven fashion has prompted explosive growth in a myriad of applications. That said, despite their popularity, there are still facets of these networks that...
Recent encouraging advances in computer vision and natural language understanding shed light on a very interesting yet challenging task: asking and answering questions about a given image (VQA). The study of this research problem is still in its infancy. Most existing VQA methods are neural network-based (NN-based) solutions that pursue...
While the entire silicon industry has been blooming under Moore’s Law for decades, conventional digital implementation is approaching the “stall” of Moore’s Law due to many physical design limitations. Technology innovation now is going to take a different direction. Given the increasing demand for emerging applications' computational capacity, it is...
This thesis studies the distributed optimization of protocols and linear precoding in multiple-input multiple-output (MIMO) wireless networks. We consider cellular systems including millimeter wave (mmWave) systems, frequency-division duplex (FDD) systems, and wideband time-division duplex (TDD) systems. Firstly, for mmWave systems, we design an efficient beam training protocol with multiple access...
The study and design of machines that are able to analyze the auditory scene and organize sound into parts that are perceptually meaningful to humans is referred to as machine hearing. Such machines are expected to distinguish between different sound categories (e.g., speech, music, background noise), focus on a sound...
Colloidal crystals are promising candidates for nanophotonic applications due to their strong interactions with light and the capability to tailor such interactions through crystal design and engineering. DNA-programmable assembly, in particular, allows for precise structural control down to the sub-nanometer length scale. In this thesis, ways of designing, synthesizing, and...
Radiofrequency ablation is a minimally-invasive treatment method that aims to destroy undesired tissue by exposing it to alternating current in the 100 kHz to 800 kHz frequency range and heating it until it is destroyed via coagulative necrosis. Ablation treatment is gaining momentum especially in cancer research, where the undesired...
Lasers and optical resonators have been widely utilized in precision metrological devices, such as gyroscopes, accelerometers, and gravitational wave detectors. To meet the requirements for a variety of applications, both of the slow light effect and the fast light effect have been applied to the lasers and optical resonators to...
The electric grid is changing rapidly with a proliferation of new technologies being integrated. There is a need to analyze the growth in technologies to help move towards a carbon-free electricity sector such as renewable generation and large scale battery installations. This is occurring at the same time as the...
Photonics are useful in applications where high-bandwidth and low-loss interlinks are desired. One of the key components of a photonic interlink is an optoelectronic modulator which is used to encode data from an electrical signal on to an optical carrier. Many of the optoelectronic modulators typically used require integration with...
Sub-wavelength matter’s interaction with far-field light is highly relevant for both fundamental scientific research, as well as many commercial, medical, and defense applications. For example, quantum computation depends on single identical photons produced by quantum dots characterized by far-field sources. Exoplanet detection uses cameras on Earth comprised of micron sized...
In modern electronics, thermal management becomes one of the most crucial factors in the determination of the performance, quality and lifetime of devices. Especially with the development of internet of things and the digitization of worldwide information, the need for storage of giant amount of data and processing with fast...
Next generation cellular networks are expected to support a massive data traffic volume and satisfy a vast number of users that have latency-critical quality-of-service expectations. Towards serving this demand, it is envisaged that the interference management problem will be the main bottleneck due to the likeliness of a heavily interfering...
Object Detection is a core computer vision problem and can facilitate many image understanding problems. Object Detection has witnessed significant progress in the past decade especially after deep learning is successfully applied to this field. Most of the detection models focus on generalizing the trained model to unseen samples of...
In recent years, machine learning on graphs (or networks) has gone from a niche topic with only a few active researchers worldwide, to a heavily invested field with novel use cases for dealing with relationships and/or interactions within complex systems in the natural and social sciences. Traditionally, choosing the right...
Originally motivated by the emergence of networked systems lacking central coordination such as multiprocessors, wireless sensor networks and smart grids, the study of distributed optimization algorithms has been an active field of research spanning multiple decades. More recently, the rapid growth in the availability of high-dimensional datasets has posed the...
X-ray imaging at nano and micro-scale is of great importance for the material science and defense industry. Large penetration depth and low wavelength of x-rays offer an important potential to image objects at high resolution and in a non-invasive process. While the ever-growing community is pursuing novel applications and looking...
We consider data-driven approaches for universal texture modeling via generative adversarial networks and inversion methods. We investigate the properties of the learned representation spaces and demonstrate that a strong link between texture analysis and synthesis is the key to successful texture modeling. First, we visit the problem of texture synthesis...
Since Infrared radiation was discovered in 1800s, the research and applications on the infrared regime have been continually developed. The infrared detectors are the key technology in these applications and have been successfully used for medical imaging, light detection and ranging (LiDAR), free-space optical communication, target tracking and object identification...
Since Infrared radiation was discovered in 1800s, the research and applications on the infrared regime have been continually developed. The infrared detectors are the key technology in these applications and have been successfully used for medical imaging, light detection and ranging (LiDAR), free-space optical communication, target tracking and object identification...
Visual localization is a critical capability for autonomous systems, enabling them to accuratelyestimate their position and orientation within an environment using visual data. This thesis focuses
on achieving a robust and reliable visual localization on both local and global level to enhance
localization performance in a wide range of environments....
We consider data-driven approaches for universal texture modeling via generative adversarial networks and inversion methods. We investigate the properties of the learned representation spaces and demonstrate that a strong link between texture analysis and synthesis is the key to successful texture modeling. First, we visit the problem of texture synthesis...
Mission-critical systems are those imperative systems whose failures can result in catastrophic consequences. Traditional techniques, such as manual investigation and testing, cannot ensure the absence of errors and security vulnerabilities within these systems. This dissertation leverages formal methods to comprehensively examine several mission-critical systems and their essential components. For each...
The field of distributed optimization algorithms is wide and growing, and new techniques for categorizing and analyzing existing algorithms are continually being developed. In this Thesis, we leverage control theoretic analysis and block diagram interpretations for existing algorithms to synthesize entirely new families of algorithms. These new algorithm families have...