Physical Sciences and Mathematics Commons^™

Improving Cancer Diagnosis And Patient Outcomes With Deep Learning Models, Mariana Arriz-Jorquiera

USF Tampa Graduate Theses and Dissertations

Cancer care depends on timely and reliable decisions, from detection and diagnosis to treatment planning and patient monitoring. These decisions are often made under uncertainty because medical images and healthcare data may be noisy, incomplete, or difficult to interpret. In breast cancer imaging, ultrasound is widely used because it is safe, accessible, and complementary to other imaging modalities. However, variations in image quality, acquisition conditions, and noise can obscure lesion boundaries and texture, affecting human interpretation and artificial intelligence reliability. This dissertation develops deep learning, image-analysis, and optimization methods to improve healthcare decisions under imperfect information. Its primary focus is …

Toward Intelligent Machines: Conscious Learning And Hardware-Accelerated Ai, Pavia Bera

USF Tampa Graduate Theses and Dissertations

Artificial intelligence systems excel at narrow, well-defined tasks but remain brittle at theboundaries of their training distributions: they cannot quantify uncertainty, adapt continuously to non-stationary data, or operate efficiently on energy-constrained hardware. This dissertation addresses these limitations through four coordinated contributions spanning probabilistic learning algorithms, biologically inspired temporal memory, cross-entity warning propagation via distributed associative memory, and spintronic processing-in-memory.

The first contribution introduces Boosted Bayesian Neural Networks (BBNNs), which extend standard mean-field variational inference by iteratively constructing a mixture posterior through Boosting Variational Inference. On five clinical medical classification datasets, BBNNs achieve superior uncertainty calibration—lower Negative Log-Likelihood and Expected Calibration …

Autoencoders As Classifiers Trained On Single Sources Of Radiographic Images For Generalizability Across Unseen Sources, Ryan M. Putney

USF Tampa Graduate Theses and Dissertations

Artificial neural networks trained to classify X-ray images according to disease state will learn to distinguish between technical or procedural variations in the images rather than features relevant to the disease. For example, the model might learn to recognize the machine that captured the image or to distinguish an image taken while the patient is lying supine or standing upright. The present work is aimed at using autoencoders as a generalizable classifier to detect COVID vs pneumonia (PNA) X-ray images. The first experiment was to find an architecture for a fully convolutional autoencoder (CAE) and for a convolutional autoencoder with …

Multi-Modal Survival Prediction On Breast Cancer Mammograms And Enabling Multi-Institutional Collaborations With Federated Learning, Nikolas Koutsoubis

USF Tampa Graduate Theses and Dissertations

Cancer remains one of the leading causes of mortality worldwide, and machine learning is well positioned to leverage the large volumes of routinely collected clinical and imaging data to improve patient outcomes. Realizing this potential at scale requires three capabilities that current practice does not yet deliver in combination: models that integrate the multiple data modalities clinicians use, training procedures that respect institutional data-sharing constraints, and tooling that enables sharing of de-identified data when federated approaches are not sufficient. This dissertation develops methods and infrastructure addressing each of these capabilities in the context of breast cancer and oncology more broadly. …

Building Trustworthy Information Systems: A Unified Framework For Comparative Risk Detection, Parisa Momeni

USF Tampa Graduate Theses and Dissertations

Risk detection in large scale information systems increasingly depends on heterogeneous data generatedby both centralized and distributed ecosystems. While centralized systems provide curated and validated reports, distributed environments produce large-scale and real-time observational evidence. Existing computational approaches analyze these ecosystems in isolation, limiting systematic comparison of risk repre-sentations across heterogeneous sources.

This dissertation presents a unified computational framework for comparative risk detection across centralized and distributed information systems. The framework provides a domain independent methodology for transforming heterogeneous risk reporting data into comparable multidimensional representations. To enable interpretable comparison of heterogeneous risk distributions, this work introduces the Geometric Overlap Score …

Seeing Around Corners: An Indirect Light Transport Decomposition Framework For Fusing Physics And Learned Priors, Fadlullah Raji

USF Tampa Graduate Theses and Dissertations

Non-line-of-sight (NLOS) imaging, or seeing around corners, is the ability to recover information about objects hidden from direct view and remains one of the most compelling challenges in computational imaging. Existing approaches fall broadly into two categories: active and passive. Active time-resolved methods achieve impressive performance but require specialized pulsed laser hardware and ultrafast detectors, making them expensive and limited by slow measurement acquisition. Passive NLOS methods, which instead exploit the subtle soft shadows (penumbrae) cast by a hidden scene onto a visible matte surface, have recently emerged as a practical alternative. However, existing passive approaches are largely limited to …

Language Models For Oncology Clinical Text: How Model Architecture And Data Strategies Shape Tumor Phenotype Extraction And Disease Progression Detection, Thanh Duong

USF Tampa Graduate Theses and Dissertations

The rapid growth of electronic health records (EHRs) has created new opportunities to apply machine learning to clinical data.However, a large portion of important clinical information is still stored in unstructured text, such as pathology reports, radiology reports, and longitudinal clinical notes.These documents contain key details about tumor characteristics, diagnoses, treatments, and patient outcomes.Extracting structured and useful information from this text is challenging due to complex medical language, varied document formats, and the need to combine information across multiple reports over time.This dissertation studies how language models can be designed and adapted to better extract and use oncology-specific information from …

Mapping Seafloor Habitats And Characterizing Demersal Reef Fish Communities On The West Florida Shelf Across Multiple Spatial Scales Using Multibeam Sonar And Underwater Video, Alexander R. Ilich

USF Tampa Graduate Theses and Dissertations

In this dissertation, I examine the role of spatial scale in deriving seafloor terrain attributes, modeling benthic habitat, and analyzing ecological patterns of the demersal reef fish communities on the West Florida Shelf (WFS), with implications for improving predictive habitat mapping and understanding fish-environment relationships. Spatial scale plays a central role in benthic habitat mapping and ecological inference, influencing how terrain attributes are derived, how habitats are modeled, and how ecological responses are manifested. This work integrates multiscale terrain analysis, acoustic remote sensing, and community ecology to evaluate how spatial scale influences both physical habitat representation and ecological analysis.

Chapter …

Portable Trace Gas Analysis With Multipass Cavity Raman Scattering, Charuka Muktha Arachchige

USF Tampa Graduate Theses and Dissertations

The continual increase in the production and utilization of chemicals across a growing range of industrial, environmental, and medical applications necessitates accurate and efficient measurement of molecular composition. Trace gas detection is particularly critical in industrialized settings, where the identification of colorless and odorless gases is essential for ensuring operational safety and regulatory compliance. Recent advances in optical instrumentation have positioned spontaneous Raman scattering as a promising analytical technique for trace gas analysis, with multipass cavity enhancement providing a cost-effective pathway to high detection sensitivity. However, existing implementations remain confined to laboratory-scale optical table setups, limiting their applicability in field …

Designing For Fitness And Resilience In Human Artificial Intelligence Systems, Thomas R. Gill

USF Tampa Graduate Theses and Dissertations

Over the last decade, new artificial intelligence models, frameworks, and applications have emerged that have radically changed the socio-technical landscape. These new technologies represent both great opportunities and great potential risks. Due to the recency of their emergence, there is little known about the longevity and long-term repercussions of artifacts powered by new artificial intelligence technology. In this dissertation, I evaluate A.I. and A.I.-based artifacts through the lens of the fitness-utility model, a tool developed by Gill and Hevner (2013) for the evaluation of an artifact's ability to survive and reproduce over long time horizons. In so doing, I also …

Photoluminescent Studies Of Metal-Organic Frameworks For Small Molecule Sensing, Julia T. Dematteo

USF Tampa Graduate Theses and Dissertations

Metal–organic frameworks (MOFs) are highly tunable nanoporous materials with broad applications in gas separation, drug delivery, light harvesting, and chemical sensing. The incorporation of photoactive components into MOFs enables the development of optical sensors capable of detecting a wide range of analytes. Porphyrins and metalloporphyrins are particularly attractive for such applications due to their high molar absorptivity, strong emission quantum yields, and versatile interactions with chemical species.

In this work, two porphyrinic MOFs, PCN-222 and MOF1(Cd), are investigated. Both frameworks utilize tetrakis(4-carboxyphenyl)porphyrin (TCPP) as the organic linker, imparting optical functionality to the materials. Integration of TCPP into the framework induces …

Risk-Aware Deep Reinforcement Learning In Portfolio Optimization, Shimin Zhang

USF Tampa Graduate Theses and Dissertations

Portfolio optimization is important in investment, with the purpose of maximizing profit whilemanaging risk. The traditional portfolio optimization method, Modern Portfolio Theory, is based on the assumption that returns are normally distributed, which is always violated in practical financial market settings. In addition, traditional approaches to portfolio optimization are mostly designed as static optimizations and fail to account for the nonlinearity and non-stationarity of contemporary financial markets. Recent developments in deep reinforcement learning have attracted considerable attention for treating portfolio optimization as a sequential decision-making process. Traditional portfolio optimization methods usually evaluate risk based on the variance of the returns. …

Van Der Waals Interactions Through The Lens Of 2d Materials With Emphasis On Many-Body Effects, Thi Xuan Diem Dang

USF Tampa Graduate Theses and Dissertations

This dissertation addresses the long-standing challenge of accurately and efficiently modeling long-range electron correlations, with a particular focus on van der Waals (vdW) interactions. These interactions play an essential role in predicting the structure, stability, and functionality of molecular systems and condensed matter materials. Although Density Functional Theory (DFT) has become a robust cornerstone of computational materials science, traditional formulations of the theory frequently fail to capture dispersive interactions, leading to significant errors in determining interlayer distances, binding energies, and stacking configurations. These limitations become particularly pronounced in layered materials and vdW heterostructures (HSTs), where weak long-range correlations are sensitive …

Photophysical Behavior Of Ruthenium-Based Complexes: A Study Of Ligand Variation And Encapsulation In Metal-Organic Frameworks, Delaney S. Sellers

USF Tampa Graduate Theses and Dissertations

Ruthenium (II) polypyridyl complexes have emerged as a prominent class of compounds in inorganic photochemistry due to their structural robustness, reversible redox chemistry, and tunable excited-state dynamics. Central to the investigation of these systems is the ability to manipulate the triplet metal-to-ligand charge transfer state (3MLCT). In the context of photoactivated chemotherapy (PACT), the strategic deactivation of this MLCT state to populate a dissociative triplet ligand field state (3LF) can enable the controlled, light-triggered release of caged cytotoxic agents. This work focuses on understanding the caging mechanism of various ligands to optimize the eventual delivery of cytotoxic ligands. In this …

Development Of A Coupled Hydrological-Nitrogen Modeling Framework For Urban Stormwater Pond Analysis, Tione Grant

USF Tampa Graduate Theses and Dissertations

Urbanization impacts the hydrological and biogeochemical processes that regulate water quality in downstream ecosystems, leading to increased stormwater volume and nitrogen loads in receiving aquatic environments. Although stormwater ponds are designed as simple hydraulic storage basins, they function more like managed ecosystems within urban drainage systems, offering both hydraulic attenuation and passive nutrient treatment. However, nitrogen removal efficiency varies significantly and depends on interactions between hydrological and biogeochemical factors. This thesis details the development, calibration, validation, and sensitivity analysis of a coupled hydrological-nitrogen model framework for Aaran’s Pond, an urban stormwater pond in Hillsborough County, Florida.

A process-based water budget …

Trophic Structure Of Reef-Fish Assemblages In The Eastern Gulf Of Mexico Varies By Depth And Reef Type, Jessica L. Van Vaerenbergh

USF Tampa Graduate Theses and Dissertations

Globally, marine ecosystems are increasingly threatened by anthropogenic stressors, leading to reef degradation, changes in reef-fish assemblages, and altered trophic structure. In this study, I investigated reef-fish underwater visual survey data collected over a decade (2013-2023) from paired natural and artificial reefs in the eastern Gulf of Mexico. I applied the novel Normalized Reef Status Index (NRSI) to evaluate how biomass was distributed across the three trophic categories (i.e., Lower Trophic Position (LTP; 2.0-2.9), Central Trophic Position (CTP; 3.0-3.9), and Upper Trophic Position (UTP; ≥4.0). This index is a metric to assess the ecological status of reef systems by investigating …

Development And Evaluation Of The East Florida Coastal Ocean Model (Efcom), Orion B. Scharton-Witmer

USF Tampa Graduate Theses and Dissertations

Florida’s Atlantic coast has abundant resources in beaches, state parks, aquatic preserves, and wildlife refuges as well as densely populated coastal cities in low lying areas that are all subjected to natural disaster threats from the oceans. There is an urgent need for a high-resolution coastal ocean circulation model for this region. Based on the application of the Finite Volume Community Ocean Model (FVCOM), an East Florida Coastal Ocean Model (EFCOM) is developed, downscaling from the deep ocean, across the continental shelf, and into the estuaries. It employs an unstructured grid with horizontal resolution varying from 3 kilometers at the …

Amending Planting Media With Typha-Derived Biochar For Sustainable Horticulture, Elissa Touma

USF Tampa Graduate Theses and Dissertations

Constructed wetlands are widely used to improve water quality by removing excess nutrients from wastewater and stormwater. Nutrients are stored within wetland vegetation, particularly in fast-growing plants such as Typha. Harvesting vegetation provides an opportunity to permanently remove these nutrients while generating biomass suitable for beneficial reuse. Converting harvested biomass into value-added products such as compost and biochar can support nutrient recovery and sustainable biomass management. In addition, increasing concerns regarding the environmental impacts of peat extraction have created interest in renewable alternatives for horticultural growing media. Therefore, the objective of this study was to evaluate the potential of harvested …

Modeling And Mitigating Stale Hardcoded Secrets In Version Control History, Katarina Valentine Capalbo

USF Tampa Graduate Theses and Dissertations

Hardcoded secret vulnerabilities remain a growing and persistent problem that can be difficult to mitigate once exposed. While there has been significant research and advancements in identifying and preventing hardcoded secrets, less attention has been given to understanding the risks of leaving these secrets behind in version control history, as well as analyzing the sanitization of hardcoded secrets. These challenges present a growing gap between the risk and ability to mitigate and sanitize existing secret exposures. This thesis begins to address this gap by formalizing a threat model for hardcoded secrets that persist in Git version control history after the …

Morphodynamic Evolution Of Midnight Pass, West-Central Florida, Sydney C. Scott

USF Tampa Graduate Theses and Dissertations

This study takes advantage of a rare opportunity provided by the reopening of Midnight Pass due to two consecutive hurricanes in 2024, to examine the morphologic evolution of a newly reopened inlet and subsequent beach-inlet interactions. Historical aerial photos since the 1940s were collected and analyzed to understand the last closure of Midnight Pass, and to gain knowledge on the future of the newly reopened inlet. Time-series topography and bathymetry survey of the beach-inlet system were conducted bimonthly to quarterly for the first year and a half after the reopening, with the goals of quantifying the morphologic changes and understanding …

The Architecture Of Chemical Understanding: How Representation Selection, Ordering, And Feature Salience Shape Students' Conceptions In Chemistry, Isaiah Nelsen

USF Tampa Graduate Theses and Dissertations

Chemical representations play a central role in how students learn and reason aboutchemistry. While representations are routinely used in chemistry classrooms, students often struggle to extract relevant information, connect representations to underlying chemical principles, and apply this information to problem-solving. This dissertation investigates the role of representations in supporting students’ conceptual understanding and reasoning across general and organic chemistry through three qualitative studies.

The first study in this work explores how variation in chemical representation influences how students understand foundational chemistry principles. This study sought to characterize how second semester general chemistry students approach dipole–dipole interaction tasks with four distinct …

New Developments In Space-Filling Designs, Xiankui Yang

USF Tampa Graduate Theses and Dissertations

This dissertation presents three methodological advancements to improve the construction of space-filling designs for meeting different needs of computer experiments. Traditional space-filling designs focus on achieving uniform coverage in the input space, ensuring that design points are spread evenly throughout. However, in some scientific and engineering applications, varied density of design points may be desired for more efficient data collection when prior knowledge implies different emphases. In other cases, ensuring good coverage and/or spread of the response values allows better performance of fitted models in the next stage of applications. Many processes involve variation in response values. Therefore, incorporating variation …

Unquaint Pigs’ Stakeholder Perspectives On Wild Swine In Central Western Florida, Tyler Koerner

USF Tampa Graduate Theses and Dissertations

The Anthropocene presents important questions for how to address the continuous transferal of new species into new spaces and the cascading impacts of environmental transformations. Novel ecosystems present one such outline for conservation that acknowledges the modification of historic ecosystems and the social entanglements that arrive with new species. I argue that novel ecosystems can benefit from further anthropological integrations that aid in describing the entanglements of introduced species and the pursuit of best managerial outcomes. For wild swine in Florida, the adoption of a novel approach is especially relevant because of entanglements with historic and modern Floridian stakeholders and …

Theory And Applications Of Natural And Nature-Based Solutions In Estuarine Environments, Elizabeth L. Royer

USF Tampa Graduate Theses and Dissertations

This dissertation focuses on the theory and application of Nature-based Solutions (NbS), through three unique case studies. This study explores how the broad and interdisciplinary NbS framework can be applied to mitigate common coastal hazards. This framework considers the environment, economics, and social wellbeing, equally in the design and implementation of a solution. The current paradigm, working against nature, which is commonly seen in more passive approaches to hazard mitigation, like grey infrastructure (e.g. a seawall to protect a shoreline against wave action) does not accommodate the extremely dynamic environment. As perspectives shift to “working with nature” NbS can be …

Iron Deficiency And Depressive Symptoms: Effects Of Racial And Ethnic Disparity In Two Reproductive-Aged Us Women, Alexis Monkhouse

USF Tampa Graduate Theses and Dissertations

Problem: Reproductive- aged women are one of the populations most at risk for iron deficiency and depression in the United States. While many studies have looked at the relationship between these two illnesses, none have explored it from a biocultural framework, examining how race/ethnicity affects this relationship. Using data from NHANES, this thesis examined the relationship between iron status (total body iron) and depressive symptoms (PHQ-9) among reproductive-aged women in the U.S. and how race/ethnicity affects it. Methods. NHANES survey data from 2005-2010 were pulled. Demographic and laboratory data were used to determine eligibility, total body iron, and depressive scores. …

Chemical Design Strategies For Hybrid Metal Halide Semiconductors With Enhanced Stability And Optoelectronic Properties, Ali Azmy

USF Tampa Graduate Theses and Dissertations

Metal halide semiconductors have rejuvenated the attention of the scientific community for the last two decades owing to their photophysical and electronic properties. However, these materials have some limitations that hinder their commercialization and widespread application. One major limitation of these materials is their instability under ambient and operating conditions of moisture, head, light and radiation exposure. Here, we report multiple chemical design strategies to address the stability issues of these materials while simultaneously maintaining their exceptional optoelectronic properties. Such design strategies allowed the acquisition of the first members of the family of porous metal halide semiconductors which exhibit record …

Riemann-Hilbert Problems For A Class Of Planar Orthogonal Polynomials, Abril Arenas

USF Tampa Graduate Theses and Dissertations

Planar orthogonal polynomials of degree n are monic polynomials defined by the orthogonality relation,

∫cPn(z)Pm(z)e-V(z) dA(z) = hnδn,m.

where the integration is over the whole complex plane with Lebesgue area measure dA, and hn is a positive norming constant. In this thesis we consider the potential V: CR of the type,

V(z) = |z|2p-2Re Σm j=1 tjzj

we characterize the planar orthogonal polynomials using novel matrix Riemann-Hilbert problems. We pro-pose a Riemann-Hilbert problem of size 2px 2p when the maximal degree satisfies m ≤ p. For m = 2p, we propose a Riemann-Hilbert problem of size 3px 3p for the …

Geospatial Understanding Of Foundation Models: Self-Supervision, Robustness, And Resource-Constrained Learning, Gilbert Kibet Rotich

USF Tampa Graduate Theses and Dissertations

Research on large-scale geospatial understanding from satellite imagery remains relativelyunderexplored. Much of the field still relies on narrow, task-specific pipelines, and there is lim- ited work on developing true foundation models or on systematically evaluating how well these models generalize under domain shift, geographic variation, and real-world scene diversity. This dissertation advances foundation-model pretraining and evaluation for remote sensing along three complementary axes. First, we develop self-supervised multispectral pretrained models for satellite image classification by adapting BYOL, BarlowTwins, DINO, MoCo, and Simsiam to multispectral inputs, addressing the limited amount of curated satellite datasets relative to ImageNet. Pretraining on Eurosat and …

Secure Machine Learning In Networking Systems, Wenwei Zhao

USF Tampa Graduate Theses and Dissertations

With the rapid integration of Machine Learning (ML) into networking systems, ensuring the security and trustworthiness of these intelligent frameworks has become a paramount concern. While ML offers unprecedented capabilities in spectrum management and collaborative learning, it also introduces novel vulnerabilities that can be exploited by sophisticated adversaries. This dissertation investigates and addresses critical security challenges across three key dimensions of ML-driven networking: adversarial spectrum sensing, the security of privacy-preserving unlearning processes, and efficient post-attack model recovery.

First, we address the threat of adversarial spectrum attacks in cognitive radio networks, where malicious nodes manipulate sensing reports to disrupt spectrum access. …

Housing Affordability Analysis Of Hillsborough County, Fl, Usa – Quantitative And Geographical Analysis Using Spatiotemporal Data, Bomin Koh

USF Tampa Graduate Theses and Dissertations

Housing affordability assessments rely on the 30 percent income method and generalized linear regression (GLR)-based hedonic price modeling. Both provide broad insights but fail to capture spatial heterogeneity in affordability challenges. This study upgrades housing affordability assessment approaches by incorporating the residual income method and Geographically Weighted Regression (GWR). The primary objective of this study is to determine whether methodological improvements, residual income method and GWR, yield significantly different results and provide a more accurate and spatially adaptive understanding of affordability dynamics in Hillsborough County, Florida.

The 30 percent income method is widely used and classifies households as cost-burdened if …