Computer Science Theses and Dissertations: Recent submissions

  • Reflections of Closures 
    Sullivan, Zachary (University of Oregon, 2024-03-25)
    The idea that programs are data forms the bedrock of functional programming languages, but it is also found in object-oriented languages and recent iterations of systems languages. Since passing and returning programs ...
  • Certified and Forensic Defenses against Poisoning and Backdoor Attacks 
    Hammoudeh, Zayd (University of Oregon, 2024-03-25)
    Data poisoning and backdoor attacks manipulate model predictions by inserting malicious instances into the training set. Most existing defenses against poisoning and backdoor attacks are empirical and easily evaded by an ...
  • LEARNING-BASED LANDMARK ESTIMATION OF 3D BODY SCANS 
    Baruwa, Ahmed (University of Oregon, 2024-03-25)
    The use of anatomical landmarks spans a diverse set of applications because they are essential for understanding the human body. Several research studies have examined the correlation between body shape variations and human ...
  • Foundations of LEO Satellite Edge Computing: An Empirical Study Based on the Hypatia Simulator 
    Dinh, Tien (University of Oregon, 2024-01-09)
    Low Earth Orbit (LEO) satellite networks have gained significant attention in recent years due to their potential to revolutionize global connectivity. SpaceX, Amazon, and Telesat are the most prominent players aiming to ...
  • Improving Cross-Lingual Transfer Learning for Event Detection 
    Guzman Nateras, Luis (University of Oregon, 2024-01-09)
    The widespread adoption of applications powered by Artificial Intelligence (AI) backbones has unquestionably changed the way we interact with the world around us. Applications such as automated personal assistants, automatic ...
  • Fine-grained, Content-agnostic Network Traffic Analysis for Malicious Activity Detection 
    Feng, Yebo (University of Oregon, 2024-01-09)
    The rapid evolution of malicious activities in network environments necessitates the development of more effective and efficient detection and mitigation techniques. Traditional traffic analysis (TA) approaches have ...
  • Structure-based Models for Neural Information Extraction 
    Pouran Ben Veyseh, Amir (University of Oregon, 2024-01-09)
    Information Extraction (IE) is one of the important fields in Natural Language Processing. IE models can be exploited to obtain meaningful information from raw text and provide them in a structured format which can be used ...
  • Cryptography, Dependability and Privacy in Decentralized Systems 
    Hu, Zhangxiang (University of Oregon, 2024-01-09)
    Decentralized systems are distributed systems that disperse computation tasks to multiple parties without relying on a trusted central authority. Since any party can be attacked and compromised by malicious adversaries, ...
  • Low-Resource Event Extraction 
    Lai, Viet (University of Oregon, 2024-01-09)
    The last decade has seen the extraordinary evolution of deep learning in natural language processing leading to the rapid deployment of many natural language processing applications. However, the field of event extraction ...
  • Advancing Clinical Natural Language Processing through Knowledge-Infused Language Models 
    Lu, Qiuhao (University of Oregon, 2024-01-09)
    Pre-trained Language Models (PLMs) have shown remarkable success in general-domain text tasks, but their application in the clinical domain is constrained by specialized language, terminology, and a lack of in-depth ...
  • On the Multi-Fractal Nature of Observed IP Addresses in Measured Internet Traffic 
    OConnor, Walton (University of Oregon, 2023-07-06)
    We examine the presence of multifractal properties in the spatial structure of observed IPv4 addresses in measured Internet traffic. A collection of traffic samples from a variety of network settings are assembled and their ...
  • Algorithms for Permutation Groups and Cayley Networks 
    Blaha, Kenneth D. (University of Oregon, 1989-09-06)
    Bases, subgroup towers and strong generating sets (SGSs) have played a key role in the development of algorithms for permutation groups. We analyze the computational complexity of several problems involving bases and ...
  • General Purpose Flow Visualization at the Exascale 
    Yenpure, Abhishek (University of Oregon, 2023-03-24)
    Exascale computing, i.e., supercomputers that can perform 1018 math operations per second, provide significant opportunity for improving the computational sciences. That said, these machines can be difficult to use ...
  • Understanding and Adapting Tree Ensembles: A Training Data Perspective 
    Brophy, Jonathan (University of Oregon, 2023-03-24)
    Despite the impressive success of deep-learning models on unstructured data (e.g., images, audio, text), tree-based ensembles such as random forests and gradient-boosted trees are hugely popular and remain the preferred ...
  • Double-Oracle Deep Reinforcement Learning for Handling Exponential Action Space in Sequential Stackelberg Security Games 
    Tan, Czander (University of Oregon, 2022-10-26)
    Standard Stackelberg Security Games (SSGs) assume attackers to be myopic players that select only a single target based on the defender's strategy. In this paper, we consider sequential SSGs, in which attackers launch ...
  • Efficient Sparse Neural Network Training 
    Shvedov, Konstantin (University of Oregon, 2022-10-04)
    Developments in neural networks have led to advanced models requiring large amounts of training time and resources. To reduce the environmental impact and to decrease the training times of models, acceleration techniques ...
  • The Time Slice Selection Bake-off 
    Kawakami, Yuya (University of Oregon, 2022-10-04)
    As the size of data from scientific simulations grows, the ability to identify key time steps in a simulation has emerged as a key challenge. In response, a number of time slice selection methods and algorithms have been ...
  • Performance Observability and Monitoring of High Performance Computing with Microservices 
    Ramesh, Srinivasan (University of Oregon, 2022-10-04)
    Traditionally, High Performance Computing (HPC) softwarehas been built and deployed as bulk-synchronous, parallel executables based on the message-passing interface (MPI) programming model. The rise of data-oriented computing ...
  • Defending Against IoT-Enabled DDoS Attacks at Critical Vantage Points on the Internet 
    Sisodia, Devkishen (University of Oregon, 2022-10-04)
    The number of Internet of Things (IoT) devices continues to grow every year. Unfortunately, with the rise of IoT devices, the Internet is also witnessing a rise in the number and scale of IoT-enabled distributed denial-of-service ...
  • Exploring the Reformulation of NLP Tasks as Text Generation Tasks 
    Hasan, Rasti (University of Oregon, 2022-10-04)
    In recent years, NLP classification tasks have been reformulated as text generation tasks in the form of text-to-text transformer-based models that achieve state-of-the-art performance by better utilizing pre-trained ...

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