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...
Human communication has become increasingly reliant on systems made and managed by large technology companies like Google, Apple, Twitter, and Meta (formerly Facebook). These systems offer people many benefits, but they also present new challenges for society. In recent years, researchers, lawmakers, and journalists have suggested that large technology companies...
This dissertation introduces several novel computational imaging techniques that capture and analyze the 3D surface shapes and internal layered materials. The research proposes user-friendly and non-invasive imaging systems, constructed using only commercial off-the-shelf (COTS) components, which provide accurate measurement of 3D information that was previously inaccessible. The dissertation focuses on...
Due to their widespread applicability, graphs and networks appear in various contexts. The increasing scale of graphs encountered in the real-world requires the developmentof efficient algorithms that run reasonably fast and produce close to optimal solutions.
The main focus of this thesis is the development of fast graph algorithms for...
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...
Many computing technologies are primarily useful because of the existence of some set of data created by people, intentionally in some cases and unintentionally in others. For instance, technologies like search engines, recommender systems, classifiers, and language models are all dependent on digital records of things people have said, done,...
A massive amount of data is generated every second all around the world. Machine learning becomes the most attractive solution to consume the data fuel and transform it into productivity. It has yielded great results in many fields, such as healthcare, marketing, finance, etc. Machine learning models are usually designed...
Public-facing data-driven technologies such as social media platforms and search engines rely on data producers, such as users and crowd workers, to be feasible and financially sustainable. Recently, it became clear that the goals of these data-driven technologies do not always align with those of the public, causing public backlashes...
While there is high demand for university computer science (CS) courses, students often struggle when learning to program. Prior work has identified that student perceptions of their programming ability may contribute to these challenges. For example, studies show that students often perceive that they do not belong, are not capable...
The current view in neuroscience holds that the brain, together with its sensory and motor structures and the environment, form a closed-loop system – a sensorimotor loop – in which the brain receives information from the environment and converts it into a motor response while simultaneously making predictions about future...
Memory management and address translation need significant optimizations in order to not behindrances in the near future. Currently, plenty of work has started to address issues within the
current abstraction of the hardware-software codesign of paging. I argue that a new abstraction
is needed in order to properly address this...