The trend towards higher resolution, faster refresh rate active-matrix liquid-crystal displays (AMLCDs) as well as the emergence of active-matrix organic light-emitting diode (AMOLED) displays is driving the demand for amorphous oxide semiconductor thin-film transistors (AOS TFTs) with higher mobility. A physics-based model for carrier transport in an amorphous semiconductor is...
The ubiquity of high quality video and proliferation of mobile devices has contributed to an unprecedented rise in video consumption. HTTP, in conjunction with adaptive streaming, has become the de facto mechanism for delivering the vast majority of video as it readily caters to heterogeneous networks and devices. This dissertation...
Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the...
Many large-scale data analysis applications involve data that can vary over both time and space. Often the primary goal of analyzing spatiotemporal data is identifying trends, movements, and sudden changes with respect to time, location, or both. This can include a variety of applications in economics (housing prices, unemployment, job...
In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
Cryptographic obfuscation is a powerful tool that makes programs “unintelligible” yet still runnable. It essentially gives programs the ability to keep secrets. The practical applications of obfuscation range from keeping secrets in banking applications to preventing software theft to providing secure messaging applications. The cryptographic applications of obfuscation are also...
Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
It is possible to purchase, for as little as $10,000, a cluster of computers with the capability to rival the supercomputers of only a few years ago. Now, users that have little to no experience developing distributed applications or managing a cluster are in a position to do so. To...
Ecological domains seeking to understand the environment and the behavior of species have received little attention in machine learning (ML), despite the fact that environmental changes have a significant impact on humans as well as ecosystems. Some ecological problems can be formulated similarly to other common ML applications, but there...
Low-power receivers (RX) with 100$\mu W$-scale power consumption can enable several power/energy-constrained IoT applications. However, achieving sensitivity, interferer tolerance and wide operating range with low power presents a challenge for existing architectures, particularly those constrained to highly integrated solutions without high-Q off-chip components. Existing solutions rely heavily on high quality...
Due to a lack of grain boundaries, an amorphous metal thin film (AMTF) possesses advantageous mechanical properties and enhanced chemical stability that is potentially useful for thermal inkjet (TIJ) printing applications. The use of an AMTF as a TIJ resistor or cavitation plate could lead to a thinner TIJ cavitation...
Modern sensors are complex systems comprising multiple sub-systems such as transducers, analog and mixed-signal interface circuits, digital processing circuits, and packaging. Over the last few decades, innovations in these sub-systems combined with their increased integration in complementary metal-oxide semiconductor (CMOS) processes have led to the rapid growth in sensors for...
Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...
Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
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...
In this dissertation, we address action segmentation in videos under limited supervision. The goal of action segmentation is to predict an action class for each frame of a video. The limited supervision means ground truth labels of video frames are not available in training. We focus on three types of...
This dissertation addresses the problem of semantic labeling of image pixels. In the course of our work, we considered different types of semantic labels, including object classes (e.g., car, person), 3D depth values (in the range 0 to 80 meters), and affordance classes (e.g., walkable, sittable). Semantic pixel labeling is...
In real networks, identifying dense regions is of great importance. For example, in a network that represents academic collaboration, authors within the densest component of the graph tend to be the most prolific. Dense subgraphs often identify communities in social networks. And dense subgraphs can be used to discover regulatory...
One of the pervasive problems arising in our modern, digital world surrounds data breaches where an adversary, through zero-day exploitations, phishing, or old-fashioned social engineering attacks, gains access to a service’s data stores. Our society increasingly relies on these cloud-based services for everything from our taxes to personal communication. As...