Assistive robotics focuses on human-robot systems that provide physical support and assistance to the elderly and people with motor-impairments. While assistive machines, such as the powered wheelchair, can significantly enhance the functional independence of individuals, many users are challenged by their direct operation, the manner in which such systems are...
Citizen media literacy is essential in a democratic society, particularly in the online environment where valid media sources have proliferated alongside purveyors of fake news. This dissertation explores technologies that automatically detect aspects of bias in news articles, with the ultimate aim of leveraging them to augment media literacy. It...
Historically, there have been large disparities in the degree to which different communities have access to resources and representation within society. With the increased availability of the internet and the growth of user-generated content platforms like Twitter and Wikipedia, there are opportunities to alleviate some these long-standing barriers to access...
Deep neural networks have shown impressive performance for many applications. In this dissertation, leveraging the capabilities of neural networks for modeling the non-linearity exists in the data, we propose several models that can project data into a low dimensional, discriminative, and smooth manifold. The suggested models can transfer knowledge from...
Many volunteer communities rely on technological systems to help their members connect, collaborate and learn the norms of how to participate in the organization. This dissertation presents research that examines technological interventions designed to support participation in three different volunteer-run communities, all of which have porous boundaries, and allow volunteers...
Neural networks have revolutionized the field of computer vision since they provide solutions to a number of previously unsolved problems and achieve promising performance both in terms of accuracy and computational efficiency. It has increasingly become recognized as providing high performance for applications as diverse as image classification, object detection,...
The Operating System (OS) kernel is a key component of modern computing infrastructure, yet it is prone to numerous vulnerabilities, many of which cause memory corruptions that can be exploited by attackers to perform malicious activities. While various techniques have been introduced to secure the Linux kernel, it still constantly...
Clustering is a fundamental task in unsupervised learning, which aims to partition the data set into several clusters. It is widely used for data mining, image segmentation, and natural language processing. One of the most popular clustering methods is centroid-based clustering, including k-medians and k-means clustering. k-medians and k-means clustering...
Performing complex reasoning has been a long-standing challenge in artificial intelligence (AI).This thesis describes a class of AI systems designed to reason, extract knowledge, and answer
questions on various domains such as process understanding, elementary science, and math word
problems. Our approach differs from traditional logical reasoning systems since we...
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...