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Leveraging Population-Based Modelling Approaches to Inform Respiratory Disease Prevention
Get PDFSevere acute respiratory syndrome 2 (SARS-CoV-2) and pneumococcal disease are vaccine-preventable but remain leading causes of morbidity and mortality in young children and older adults. In this dissertation, I present three population-based studies which inform respiratory disease prevention using public health surveillance data.
In a population-based cohort study, I linked reported SARS-CoV-2 cases with vaccination records in Ontario, Canada. I found that vaccination is associated with lower odds of hospitalization among adolescent and pediatric Omicron (B.1.1.529) SARS-CoV-2 cases, even when the vaccines do not prevent infection.
I developed and analyzed a dynamic pneumococcal transmission model fit to age-specific invasive pneumococcal disease (IPD) incidence in Canada. Using the fitted model, I found that the use of 13-valent pneumococcal conjugate vaccines in pediatric populations prevented 1,275 IPD cases across the population, with the majority of cases averted in older adults.
In a self-matched case-crossover study, I estimated the impact of acute changes in influenza A, influenza B, and respiratory syncytial virus (RSV) activity on IPD risk. I found that influenza A activity and influenza B activity are independently associated with increased IPD risk. However, the co-circulation of influenza A and B reduced the impact of both viruses. RSV activity was positively associated with increased IPD risk only in the presence of increased influenza activity.
Overall, these results contribute to our understanding of vaccine-preventable respiratory diseases in Canada. These results can inform strategies to prevent morbidity and mortality from respiratory diseases.Ph.D
Credit Portfolio Management of Corporate and Commercial Loans with Robust Machine Learning Methods
Get PDFThis thesis addresses critical challenges in credit portfolio risk management for financial institutions, focusing on corporate and commercial loan portfolios. This thesis comprises three main project. The first two projects are published in the Journal of Credit Risk the third project has been accepted for publication at the Journal of Applied and Numerical Optimization:
1. Credit Risk Rating Modeling: This study introduces a novel approach to credit risk rating for corporate entities, enabling banks to make accurate, cost-effective rating decisions while maximizing risk-adjusted returns under model uncertainty within the Basel Regulatory Framework. By leveraging ordinal information from expert-assigned credit ratings, the methodminimizes expected economic costs. Empirical results demonstrate higher returns on regulatory capital for medium-sized North American companies.
2. Distributionally Robust Optimization (DRO) in Credit Risk Management: This project applies a DRO framework to enhance credit risk management by addressing data uncertainty and model misspecification. Two applications are explored: predicting significant increases in credit risk (SICR) under the IFRS 9 Expected Credit Loss framework and managing risk limits for corporate loans. The findings show that DRO improves model robustness by accounting for distributional uncertainty, supporting more informed and regulatory-compliant decision-making.
3. Robust Contextual Bandit Method for Optimal Loan Offering: This study proposes a group-DRO-enhanced, doubly-robust contextual bandit approach to optimize loan product offerings. Tailored for high-stakes lending decisions, this method leverages historical data to design policies while mitigating biases and uncertainties. By incorporating group-based ambiguity sets and fairness constraints, such as demographic parity or equal opportunity, the approach ensures robustness against worst-case shifts in sensitive subgroups and aligns with ethical and regulatory standards. Empirical evidence from a small business credit card portfolio demonstrates significant improvements over standard methods, advancing responsibleAI in finance.
Collectively, these contributions provide advanced methodologies to enhance credit risk management, improving the modeling and management of corporate and commercial loan portfolios for financial institutions.Ph.D
Local Riverscapes and Environmental Consciousness in the Abbey of Saint-Amand: Foundations until 1097
Get PDFThis thesis explores the self-conceptualization of the monks of the northern French abbey of Saint-Amand in the diocese of Tournai with respect to how they related to the local
environment, specifically, its rivers. It seeks to determine how greatly the monks identified
themselves with the rivers Scarpe, Elnon, and Scheldt and whether or not the monks felt an
urgency to preserve these local aquatic environments in the face of human-imposed changes
on the landscape. This thesis restricts its analysis to historiographical and documentary
evidence, approaching environmental history from the carefully constructed written
perspectives of monks from the time of the abbey’s foundation to the late eleventh century.M.A
Synergistic Effects of Polyphosphoric Acid and Montmorillonite Nanoclay on the Performance Properties of Asphalt Binder
Get PDFMontmorillonite nanoclay has been used to improve asphalt binder stiffness, rutting resistance, and oxidation stability, but its moisture-induced swelling limits durability. This study evaluates polyphosphoric acid as a complementary additive to reduce swelling and enhance nanoclay performance. The acid intercalates into clay interlayers, creating a hydrophobic barrier against water ingress. Three binders were tested: neat PG 64 22, nanoclay modified, and a hybrid binder with both nanoclay and polyphosphoric acid. Performance was assessed using PG grading, multiple stress creep recovery, frequency sweep, swelling, and extended bending beam rheometer tests. The hybrid binder reduced swelling by nearly fourfold relative to nanoclay alone and showed improved rutting resistance and aging durability after thermal conditioning. However, both nanoclay and hybrid binders displayed greater physical hardening at low temperatures, indicating a trade-off between high-temperature durability and low-temperature flexibility. Overall, the hybrid system provides enhanced moisture protection and aging resistance while highlighting limitations in cold climates.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
A Multimodal Neuroimaging Study of Alcohol Use Disorder: Functional Connectivity, Endocannabinoid Metabolism and Clinical Outcomes during Abstinence
Get PDFAlcohol use disorder (AUD) is marked by dysregulation of functional connectivity (FC) which may be pertinent to symptoms during abstinence. Fatty acid amide hydrolase (FAAH), a metabolizing enzyme of anandamide, modulates frontoamygdala FC. We investigated the abnormalities of FC in AUD and whether impairments were associated with higher FAAH levels and poorer clinical outcomes. AUD and control participants completed a resting-state MRI and PET scan with the FAAH tracer, [11C]CURB. Frontoamygdala FC was significantly lower in AUD than controls, with a greater effect in severe AUD participants. In AUD, no relationship was found between FAAH and frontoamygdala FC. Frontoamygdala FC showed a significant negative correlation with mood and withdrawal symptoms. Lower frontoamygdala FC was seen in AUD, which was related to clinical outcomes, but not FAAH levels. The current study suggests that lowered FC may be clinically relevant, and the role of FAAH in regulating FC may differ in AUD.M.Sc
Proper Forcing, The P-Ideal Dichotomy, and the S-space Problem
Get PDFIn this thesis, we explore the relationship between the S-space problem and the Proper Forcing Axiom (PFA). In particular, we prove that many consequences of PFA are compatible with the existence of various S-spaces. We start by studying the notion of solid graph, first introduced by Soukup, and show this can be used to encode many objects whose existence follows from ♢ or CH. We prove that Neeman iterations preserve solid graphs, providing a general tool for preserving such objects while forcing consequences of PFA.
Next, we then introduce two new types of graph, namely (m, n)-solid graphs and HF graphs. These new notions can encode many different S-spaces, including strong HFD spaces, strong HFDw spaces, and first countable strong O-spaces. We then prove that much of the theory of solid graphs extends to these new notions, including the preservation by Neeman iterations.
From here, we are able to construct novel models of ZFC with many consequences of PFA plus the aforementioned S-spaces. Using (m, n)- solid graphs, we construct models with p = ℵ2, the Mapping Reflection Principle, the Open Graph Axiom, Baumgartner’s Axiom for ℵ1-dense sets, and all Aronszajn trees are club isomorphic. Using HF graphs, we construct models with s = ℵ1, add(M) = ℵ2, the Mapping Reflection Principle, and the P-Ideal Dichotomy. Most notably, our work provides a partial negative answer to a question of Todorcevic about whether the P-Ideal Dichotomy and b > ℵ1 implies there are no S-spaces.Ph.D
Physics-Based Modeling and Optimization of Reconfigurable Intelligent Surface-Enabled Communication Channels
Get PDFReconfigurable intelligent surfaces (RISs) enable dynamic control of wave propagation. They are a promising technology for current and future communication systems. This thesis investigates how RISs can be analyzed, modeled, and optimized, to redirect waves and bypass obstacles, thereby extending coverage into non-line-of-sight (NLoS) regions. We aim to bridge the gap between theoretical potential and real-world implementations of RISs.
Two hybrid full-wave/ray-tracing schemes are proposed to model wave propagation in radio environments with RISs. The first, a complex radar cross-section (CRCS)-based approach, addresses cases where the RIS is illuminated dominantly by one plane wave, and the receivers are in the far-field region of the RIS. The second, an equivalence principle-based method, rigorously accounts for all incident waves at the RIS and yields accurate results in both near- and far-field regions. Both methods are validated against finite element simulations of entire channel geometries and an indoor measurement. Notably, each scheme requires one full-wave simulation per RIS configuration to obtain either the CRCS or the equivalent currents.
To avoid repeated full-wave simulations, we develop a semi-analytical method that quickly computes the CRCSs. In practice, the cell-to-cell coupling in an RIS differs markedly from periodic structures, which limits the accuracy of the semi-analytical approach. To address this bottleneck, we propose a method based on convolutional neural networks (CNNs). Trained on data from full-wave simulations, the CNN rapidly predicts equivalent currents for any configuration, as well as for various incident waves and RIS sizes. Moreover, the CNN enables fast and accurate wave propagation modeling in RIS-enabled channels.
The CNN can be embedded within an optimizer, as a mutual coupling-aware evaluator of RIS scattering properties, to search for optimal codebooks/configurations that meet specific objectives. For a 1-bit RIS, we find codebooks that reduce side lobe levels or suppress quantization lobes—performance previously considered unattainable without additional hardware. We further extend codebook design to a site-specific framework. Through case studies, we show that site-specific codebooks outperform those designed without considering the deployment site conditions.
Overall, this thesis advances RIS technology by introducing new numerical modeling and optimization methods, and by providing insights that facilitate practical deployment.Ph.D
An Examination of Mental Health Service Utilization Measurement and Associations with Social Determinants of Health in Youth
Get PDFDespite the burden of mental health challenges in youth, only 25% receive necessary care. There is currently no gold standard measure to assess mental health service utilization in youth, and findings are mixed on how social determinants of health (SDOH) influence service use patterns. This thesis presents a scoping review of standalone instruments with evaluation of measurement properties used to assess mental health service use in youth, and a secondary analysis of service use and SDOH data from an ongoing prospective cohort study. The scoping review identified N=8 instruments with varying degrees of measurement property evaluation, instances of use, and services assessed. The secondary data analysis found higher rates of outpatient service use in those engaged in education, employment, or training and hospitalization among those assigned female at birth. These results add to the growing body of literature aiming to address gaps in youth mental health service use.M.Sc
The Determinants and Dimensions of Armed Group Taxation
Get PDFWhy do some armed groups tax while others do not? When they do tax, how do they develop their taxation systems, and what determines whether taxation is enforced coercively or more contractually? This dissertation investigates the prevalence, institutionalization, and nature of armed group taxation (AGT) to understand its implications for governance, legitimacy, and conflict outcomes. While taxation has long been viewed as a defining function of the state, armed groups frequently engage in taxation as part of their broader governance practices, particularly in contexts where the state is fragile, contested, or absent. Taxation is the most common governance practice of armed groups, yet it remains underexplored as a distinct wartime institution despite its potentially transformative effects.
This dissertation argues that AGT varies along three key dimensions: its prevalence, its degree of institutionalization, and the extent to which it is enforced coercively or contractually. The argument is structured around three interrelated questions: (1) When do armed groups tax? (2) When do they institutionalize taxation? and (3) When do they tax in more contractual ways? Drawing on a global quantitative analysis and a comparative case study of the Moro Islamic Liberation Front (MILF) and the Communist Party of the Philippines-New People’s Army (CPP-NPA), this research demonstrates that AGT is shaped by three primary factors: revenue imperatives, feasibility (military and organizational capacity), and community embeddedness.
The findings show that while financial pressures drive armed groups to tax, their ability to do so is constrained by military strength and organizational capacity, which are necessary for enforcing compliance. When groups lack these capabilities, taxation remains infeasible, regardless of financial need. However, even among groups that successfully institutionalize taxation, the mere existence of tax systems does not automatically lead to more contractual or reciprocal relationships with taxpayers. Instead, community embeddedness and the conditional role of non-tax revenues shape the nature of taxation. Embedded groups with access to alternative revenue sources are more likely to allocate resources toward public goods and services, reinforcing taxation as a governance tool rather than mere extraction. In contrast, groups that lack embeddedness and face acute financial desperation—particularly those without non-tax revenues—are more likely to apply more coercive taxation to wealthier taxpayers, such as foreign businesses or political actors, while engaging minimally with the broader populations. As a result, taxation by non-embedded groups is more likely to be perceived as coercive, whereas embedded groups with financial stability are better positioned to cultivate reciprocal fiscal relationships with taxpayers, towards a more contractual approach to taxation.
This dissertation makes three key contributions. First, it develops a framework for conceptualizing AGT as a distinct phenomenon, challenging the common conflation of taxation with extortion or looting. Second, it provides empirical evidence on the prevalence and institutionalization of armed group taxation, showing how taxation systems evolve over time in response to revenue pressures and feasibility. Finally, it examines the role of AGT in shaping wartime political orders, highlighting its potential to foster governance legitimacy or deepen coercion, with implications for state-building and post-conflict transitions. By treating taxation as a central component of rebel governance, this research advances our understanding of how armed groups interact with local populations and the conditions under which they develop state-like institutions.Ph.D
Revealing Additional Size-Dependent Defect Suppression Channels Governing Detectivity in InAs Colloidal Quantum Dot Photodiodes
Get PDFThis document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Nano Letters copyright © after peer review and technical editing by the publisher. To access the final edited and published work see https://doi-org.myaccess.library.utoronto.ca/10.1021/acs.nanolett.5c04477Indium arsenide (InAs) colloidal quantum dot (CQD) photodiodes combine tunable bandgaps with solution processing, offering a versatile platform for infrared detection. Using high-dynamic-range external quantum efficiency (HDR-EQE) measurements, we probe defect signatures and quantify their impact on performance. Analysis of Urbach tails and Gaussian sub-bandgap states shows that trap densities decrease with increasing nanocrystal size, exceeding predictions from simple surface-to-volume scaling and underscoring the influence of surface chemistry on bandedge disorder. These defect states affect the dark saturation current (J0), enabling us to estimate their contribution to detectivity and noise. The results connect nanocrystal size, defect population, and device performance, distinguishing intrinsic trap-mediated effects from extrinsic loss channels. We find that while intrinsic defects play a role, today’s InAs CQD photodiodes are primarily limited by contact and interface properties, highlighting these as key targets for further improvement.This work made use of the MatCI Facility supported by the MRSEC program of the National Science Foundation (DMR-2308691) at the Materials Research Center of Northwestern University. This work was supported by the Samsung Advanced Institute of Technology (SAIT), Samsung Electronics Co, Ltd