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...
In the late 2000’s, scientific studies in cultural heritage saw a great advancement in macro X-ray fluorescence (XRF) imaging of paintings. These images are used to generate elemental distribution maps, which aid in identifying chemical elements and paint pig- ments as well as their locations throughout the layers of the...
In the Maximum-a-Posteriori (MAP) Inference problem, for any given probability distribution, the goal is to find the point in the support of that distribution with the highest probability. Potts models and Determinantal Point Processes (DPPs) are probabilistic models that were introduced in the context of statistical physics several decades ago....
As our world is increasingly filled with data visualizations, having the skills to leverage data visualizations is essential for participation in society. Confident engagement with data visualizations is critical for being an educated member of society; however, research has shown that it is difficult for individuals to digest and gain...
Machine learning is seeping into every fabric in various practical domains such as autonomous driving, wearable computing, and smart buildings. However, in the actual development and integration, especially when the learning-based components are frequently included as components of large complex systems where the physical instances can be included as interactable...
Task-oriented conversational systems are becoming increasingly popular, as shown by the rise of conversational recommendation systems across multiple platforms (e.g., Google Home, Alexa, and Siri) and domains (e.g., local establishments, e-commerce, books, music, and movies). However, users are still largely limited in what preferences they can express and how, as...
The production and spread of digital news involves a wide range of actors: journalists and the organizations that employ them, social media platforms, audiences, and myriad commentators, citizen journalists, bloggers, and other actors who contribute to the news ecosystem without inhabiting an official role. These actors interact in flexible, often...