Theses

Permanent URI for this collectionhttps://uwspace.uwaterloo.ca/handle/10012/6

The theses in UWSpace are publicly accessible unless restricted due to publication or patent pending.

This collection includes a subset of theses submitted by graduates of the University of Waterloo as a partial requirement of a degree program at the Master's or PhD level. It includes all electronically submitted theses. (Electronic submission was optional from 1996 through 2006. Electronic submission became the default submission format in October 2006.)

This collection also includes a subset of UW theses that were scanned through the Theses Canada program. (The subset includes UW PhD theses from 1998 - 2002.)

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Categorical 't Hooft Expansion and Twisted Holography
(University of Waterloo, 2026-06-15) Lopez Raven, Adrian Khalil
This thesis studies ideas of Holography and 't Hooft expansions in the context of Twisted Holography. The 1st part introduces a novel entry in the Twisted Holography dictionary, associating to certain boundary operators, bulk instantonic deformations of D1-D5 brane systems in SL(2,C). From the boundary operators, we are able to extract the data of both the shape and Chan-Paton bundle of the dual brane, encoding it in a derived coherent sheaf. We then apply this construction to chiral algebras with SO and Sp gauge groups, obtaining branes with Z2 identifications consistent with conjectures relating these chiral algebras to orientifolds of the bulk B-model theory. The second part, extends the conjecture of Twisted Holography to a wide family of chiral algebras. In particular, we study boundary theories containing several βγ-systems with several U(N) gauge groups. Amongst these one has known chiral algebras arising from the twist of quiver-gauge theories, but also new chiral algebras whose dual B-model lives in non-commutative backgrounds. Using techniques from String Field Theory and Homological Algebra, we extract from these chiral algebras, algebraic properties of the conjectural dual worldsheet theories, and track how they deform under backreaction.
Representing Sexual Violence and Sexual Violence on Campus: Institutional Constructions, Student and Staff Perceptions, and Their Effects
(University of Waterloo, 2026-06-15) Goodall, Jade
Universities have increasingly been positioned as key sites of sexual violence prevention and response, yet little attention has been paid to how they construct and represent sexual violence through the institutional texts they produce. This study examines how sexual violence and sexual violence prevention are represented within university polices and prevention materials, and how these representations are perceived and understood by students and staff. This qualitative study draws on a textual analysis of 130 institutional documents and semi-structured interviews with 10 students and staff at a Southwestern Ontario university (referred to as Z University). Guided by Bacchi’s (2009) What’s the Problem Represented to Be? approach, and drawing on theoretical insights from Dorothy Smith (2005) and Patirica Hill Collins (2019), the analysis examines how sexual violence is represented, the assumptions that underpin these representations, what is left unspoken, and how these representations are taken up in practice. The findings demonstrate that sexual violence is predominately framed as a matter of legal compliance, public health education, and individual responsibility. Participants describe tensions between institutional representations and lived experience, particularly among those who feel excluded or misrepresented within dominant framings. Rather than producing generalizable claims, this study offers a critical, context-specific analysis of how sexual violence and sexual violence prevention are constructed within institutional settings and how these constructions are perceived and negotiated by students and staff.
On Initializations for NMF
(University of Waterloo, 2026-06-15) Shi, Sammy
In Ward and Kolda (2023) and Xu et al. (2024), the authors proposed a sketching based initialization for unconstrained two block matrix factorization (MF) with provable guarantee. The purpose of this thesis is to examine the limits of extending these two proof frameworks in the context of Non-negative Matrix Factorization (NMF), as well as its numerical implications. The first chapter deals with fundamentals of NMF: its formulation, the identifiability issue and guarantees, a survey of iterative methods to solve it, and finally some complexity results. In the second chapter, I will quickly go over spectral initialization techniques for matrix optimization problems, and introduce sketching, a family of randomization techniques for numerical linear algebra, with a particular focus on its uses in iterative methods. The core focus of this chapter lies at the intersection of these two topics: a sketching-based initialization for the unconstrained two-block MF problem, using either non-alternating or alternating gradient descent (GD). We will go over the proof frameworks. In the third chapter, I will present my attempts to generalize the proof frameworks to NMF and the conclusions based on the partial progress. The fourth chapter deals with numerics. We will compare the performance of different base methods in different data regimes using all of the initializations mentioned in this thesis.
Recalibrating Reality: Sensory Reweighting and Cybersickness Susceptibility in Virtual Reality
(University of Waterloo, 2026-06-15) Izadi Sokhtabandani, Siyavash
This dissertation investigates how the brain dynamically reweights sensory cues to resolve multisensory conflicts in virtual reality (VR), with a specific focus on the etiology of cybersickness. The research characterises how visual, vestibular, and proprioceptive cues are integrated and recalibrated following VR gameplay while accounting for individual differences in these processes which dictate susceptibility to sickness. Across three experiments, this work challenges the assumption that VR exposure triggers a uniform sensory shift. Experiment 1 utilised the Subjective Visual Vertical (SVV) task, finding that high-intensity exposure shifted participants' perceived upright toward gravitational vertical and away from the body axis. Crucially, individuals who demonstrated greater reweighting reported lower cybersickness, suggesting that rapid sensory adaptation acts as a protective mechanism. Experiment 2 employed the Oriented CHAracter Recognition Test (OCHART) to further tease apart the relative weighting of visual and gravitational cues. While VR exposure did not produce a uniform group-level shift in the Perceptual Upright (PU), exploratory analyses revealed that increased visual weighting post-exposure was associated with higher cybersickness, indicating that a failure to down-weight unreliable visual inputs may be maladaptive. Experiment 3 attempted to manipulate these weights by degrading vestibular reliability through stochastic electrical vestibular stimulation (EVS). Contrary to the hypothesis that reducing vestibular certainty would force a beneficial reweighting, EVS exacerbated cybersickness and increased attrition, while cue-weighting models remained unstable. Altogether, this work demonstrates that cybersickness is not merely a product of sensory conflict, but a failure of the central nervous system to successfully reweight unreliable cues. The results suggest a two-part interpretation: first, that individual differences in sensory plasticity may relate to tolerance, where greater post-VR shifts toward gravitational cues were associated with lower symptom severity in Experiment 1, though this relationship was not consistent across tasks and measures. Second, the results suggest that external disruption of vestibular signals (via EVS) may hinder rather than help adaptation. These findings provide preliminary evidence for a reweighting account of individual differences in cybersickness susceptibility and point toward personalised exposure protocols as a candidate intervention, pending replication with larger and more diverse samples.
Intersectional Incivility in Aviation: Socio-Spatial Relation, Constrained Agency, and Safety Reporting
(University of Waterloo, 2026-06-12) Ram, Angeline
Background: In Canadian air transportation organizations, employee safety reporting programs (ESRPs) are used as formal channels for all workers, including aircraft maintenance engineers and pilots, to raise occupational health and safety and aviation safety management system concerns. However, reportable issues are narrowly defined, so workplace incivility falls outside of sector safety reporting criteria. Although participation in ESRPs is framed as a moral duty within non-punitive, policy-driven safety cultures, policies do not necessarily create environments where workers feel safe to speak up. Instead, workers navigate these environments through constrained agency, intentionally remaining silent. In many cases, workers prioritize coping strategies that support their wellbeing over participation in formal reporting systems. From a labor geography perspective, this gap reflects how socio-spatial relations, shaped by culture, hierarchy, and colonial, imperial, and patriarchal legacies, normalize incivility. Though the Canadian air transportation sector has largely treated workers as a homogeneous group, further investigation is necessary to understand how socio-spatial relations, intersectional identities, and constrained agency shape workplace experiences, wellbeing, and participation in safety reporting. Objectives: Most sector literature examines gender-based incivilities experienced by women pilots through a homogeneous lens, assuming identical experiences regardless of race, occupation, immigration status, or sexual orientation. Workers’ experiences shaped by intersectional identities (race, gender, occupation, occupational status, immigration status, sexual orientation) remain under-examined. Situated within feminist epistemologies, this research asks: How do the lived experiences of air transportation workers in Ontario shape their participation in Employee Safety Reporting (ESR)? Objectives are: 1) explore how occupational identities shape air transportation workers' experiences in the workplace; 2) explore how intersectional identities shape air transportation workers' experiences in the workplace; and 3) investigate how identity-based incivility shapes ESR participation. Methodology: This exploratory qualitative research draws on labor and feminist geographies and Black intersectionality theory to expose power relations and agency. I conducted in-depth, semi-structured interviews with pilots and aircraft maintenance engineers of diverse statuses and identities. Interviews were video- and audio-recorded, transcribed verbatim, and analyzed in NVivo. Analysis used Hollinda et al.’s (2023) blended methods (summative content analysis + thematic analysis) and draws on Nash (2018) to use intersectionality as a methodological tool to generate inter-categorical profiles. Findings and Discussion: Three findings emerged: 1) occupational hierarchies shape incivility and wellbeing; 2) socio-spatial relations through incivility target intersectional identities, and shape wellbeing; and 3) incivility constrains agency, leading to coping over reporting. Workers in the same occupation are not monoliths: interlocking identities shape who is targeted, and incivility shapes how wellbeing is experienced. AMEs reported more identity-based incivility than pilots, and wellbeing impacts increased as occupational status decreased, reflecting power geometries that normalize disrespect toward subordinates. Incivility influenced wellbeing through six connected subthemes: stress and anxiety, frustration and powerlessness, exclusion, obsessing about interactions, self-doubt, and adverse effects on home life. Rather than reporting iv through ESRPs, workers, especially in lower-status roles, used constrained agency to protect wellbeing through overlapping coping strategies of adaptation, tolerance, and withdrawal. These strategies reflect a transaction in which employment security or advancement can outweigh the perceived benefits of reporting, challenging assumptions that policy requirements alone ensure participation. Conclusion: Socio-spatial relations among AMEs and pilots are shaped by hierarchical histories and colonial and patriarchal cultures that normalize identity-based incivility. When workers are targeted because of their intersectional identities, their already constrained agency becomes further limited, and they cope in ways that support their wellbeing rather than participate in safety reporting. Organizations need to integrate psychological safety into Safety Management Systems (SMS) as a foundational aspect of safety across teams and daily operations, and the sector should view workers through an intersectional lens, as occupational status and intersecting identities shape both exposure to incivility and the capacity to raise concerns. Policymakers must address the gap in which normalized incivility continues to cause distress and deter reporting. Recommendations include revising SMS and safety culture requirements to encompass employee wellbeing; training leaders and crews to recognize and address subtle incivility; and linking occupational health reports with safety data to ensure accountability, follow-up, and ongoing evaluation.
Internal conflict within Asian security arrangements
(University of Waterloo, 2026-06-12) Benjamin, Jacob
This dissertation examines a puzzle: allies and interoperable security partners that fight each other. The dissertation gathers and generates data on this confusing state of affairs and explains the factors that can cause this outcome. The dissertation consists of three papers. The first paper devises a new formula to measure the amount of internal conflict in a particular arrangement. I use this method to measure the amount of conflict in over thirty different security arrangements. The data flag anomalous arrangements, which are those alliances and interoperable security partnerships with several members that fight each other. The second paper is a case study on the Shanghai Cooperation Organisation (SCO). The SCO is a salient arrangement because five of the ten SCO members have fought another SCO member in the short span of five years. The third paper broadens the scope of this research to the Association of Southeast Asian Nations (ASEAN). While not an interoperable security partnership, ASEAN is a pertinent case study because it has claimed to be a security community; yet some of its members have fought each other in limited wars, and many members have serious contestations with other members on security issues. The findings of this research have both practical and theoretical significance. During the research design phase, I initially did not consider democratic peace theory as relevant to the dissertation’s topic; however, the findings ended up showing strong support for the significance of regime type in international relations. When there is internal conflict in security arrangements, often it is because of divergent regime types (democratic versus authoritarian regimes). Moreover, the fact that there is so much conflict within the SCO – an authoritarian security arrangement – reinforces the notion that authoritarian states are qualitatively more aggressive than democratic ones. That is, beyond waging conflict on their adversaries, authoritarian states are far more likely to wage conflicts on their so-called friends. Finally, since ASEAN has such a variety of regime types, it became clear why the association has struggled to develop deeper security commitments.
Aggregating and evaluating ambiguity in decision models
(University of Waterloo, 2026-06-12) Van Oosten, Zachary
This thesis develops new decision models under ambiguity that accommodate arbitrary reductions in the absence of ambiguity, that is, models not restricted to expected utility (EU) under pure risk (no ambiguity). A central challenge is the identifiability problem: from preferences alone, one cannot distinguish which features of the representation functional reflect the decision maker's evaluation of pure risk from those that reflect their reaction to ambiguity. To resolve this, we exogenously specify a family of unambiguous events and employ the property of partial law invariance: the DM is indifferent between unambiguous acts with the same distribution. The resulting models developed across the four chapters outlined below are relevant to decision theory, quantitative risk management, mathematical finance, and operations research. Chapter 2 studies partial law invariance in the context of risk measures. We fully characterize partially law-invariant coherent risk measures via a novel representation formula and extend the classical Kusuoka representation. Additionally, we propose new risk measures, including partially law-invariant versions of Expected Shortfall and entropic risk measures, along with tractable formulas for their calculation. Chapter 3 axiomatizes the Choquet rank-dependent utility (CRDU) model, which cleanly separates pure risk from ambiguity and reduces to rank-dependent utility in the absence of ambiguity. We show that the coupling of ambiguity perception and ambiguity attitude can be fully characterized by the matching probability, and that the supermodularity of this matching probability gives CRDU a distributionally robust interpretation. Chapter 4 distinguishes two conceptual frameworks for processing ambiguity: evaluate-then-aggregate (ETA), which first evaluates an act under each plausible model and then aggregates, and aggregate-then-evaluate (ATE), which first reduces ambiguity to a single representative distribution before evaluation. As most existing ambiguity models fall within the ETA framework, we develop and axiomatize the Choquet ATE model that generalizes both Choquet expected utility and CRDU while accommodating arbitrary pure-risk evaluations. Afterward, we provide a rich analysis of the interplay between ambiguity attitudes and risk attitudes. Chapter 5 develops a distributionally robust optimization model whose ambiguity set is derived from a Bayesian second-order belief, providing a clear separation between pure risk, ambiguity perception, and ambiguity attitude. This chapter is motivated by the observation that the smooth ambiguity model does not satisfactorily generalize to arbitrary pure-risk evaluations. A canonical construction based on distorted second-order beliefs is introduced as a tractable instance of this model, with accompanying algorithms and numerical illustrations in the context of portfolio optimization.
Aluminum-Air Batteries Across Scales: A Multiscale Framework for Electrochemical Characterization, Materials Optimization, and Electric Vehicle Integration
(University of Waterloo, 2026-06-10) Shabeer, Yasmin
Aluminum-air (Al-air) batteries have emerged as a promising energy storage technology due to their exceptionally high theoretical energy density, material abundance, and potential for low-cost deployment. However, their practical implementation remains constrained by challenges related to electrochemical performance, parasitic corrosion, electrolyte management, and system-level integration. This thesis presents a comprehensive multiscale investigation of Al-air batteries, integrating techno-economic analysis, experimental characterization, data-driven modeling, and system-level simulation to evaluate their viability as advanced energy storage systems and range extenders in electric vehicles (EVs). The study begins with a techno-economic assessment of metal-air batteries in EV applications. A comparative framework is developed to evaluate the performance of Al-air systems relative to conventional lithium-ion batteries, incorporating key metrics such as gravimetric energy density, vehicle energy consumption, and cost. The analysis shows that Al-air batteries, with practical energy densities of approximately 700-900 Wh kg⁻¹, significantly outperform Li-ion systems (150-250 Wh kg⁻¹), offering strong potential for range extension. Simulated vehicle scenarios indicate that Al-air integration can extend driving range by a factor of 2-5, depending on system configuration and operating conditions. However, these benefits are offset by trade-offs related to system complexity, auxiliary components, and cost, highlighting the need for integrated evaluation frameworks. Experimental investigations are conducted to examine the electrochemical performance of Al-air batteries under varying electrolyte compositions and operating conditions. Using a novel galvanic generator-type Al-air system with a rotating electrode configuration, multiple prototype units provided by AlumaPower were evaluated. The rotating electrode design enhances mass transport, reduces passivation, and promotes uniform anodic dissolution, enabling improved discharge stability compared to conventional static systems. Systematic experiments reveal the alkaline electrolytes, particularly in the range of 6-8 M concentration, provide optimal performance by balancing ionic conductivity and electrochemical kinetics. Peak power densities exceeding 500 mW cm⁻² are achieved under controlled conditions, while discharge tests at moderate current densities (~80-100 mA cm⁻²) exhibit stable voltage profiles in the range of 1.0-1.2 V. The results further demonstrate that increasing electrolyte concentration beyond optimal levels accelerates parasitic corrosion and hydrogen evolution, leading to reduced efficiency and highlighting the importance of electrolyte optimization. To address the critical challenge of aluminum corrosion, a data-driven predictive modeling framework is developed. Artificial neural networks (ANNs) are trained on experimental datasets to model the relationship between electrolyte composition, temperature, and electrochemical variables with corrosion metrics such as corrosion potential (Ecorr) and corrosion current density (Icorr). The ANN models achieve high predictive accuracy, with coefficient of determination (R²) values exceeding 0.99, demonstrating their capability to capture complex nonlinear relationships in electrochemical systems. To further enhance system performance, genetic algorithms (GA) and multi-objective optimization (NSGA-II) are integrated with the ANN framework to identify optimal operating conditions. The optimization results reveal trade-offs between maximizing Ecorr and minimizing Icorr, enabling the identification of optimal electrolyte conditions that balance performance and degradation. This integrated modeling approach represents a significant advancement over conventional empirical methods by enabling predictive and systematic optimization of corrosion behavior. At the system level, the thesis develops a comprehensive modeling framework for integrating Al-air batteries within EV architectures. Using MATLAB and Simulink, a dual-energy storage system is implemented in which Al-air batteries function as range extenders for lithium-ion battery packs. The system incorporates experimentally informed battery models and employs state-of-charge (SOC)-based control strategies to manage power flow between energy sources. Simulations conducted under standard driving cycles, including UDDS, WLTP, and HWFET, demonstrate that Al-air integration can significantly mitigate SOC depletion and extend vehicle range, particularly in reduced-capacity Li-ion configurations (e.g., 50% and 35% baseline energy). The results highlight the importance of control strategy design, power limitations, and system configuration in achieving optimal performance. Collectively, the findings of this thesis establish a comprehensive framework linking electrochemical behavior, corrosion kinetics, and system-level performance of Al-air batteries. The integration of experimental characterization, data-driven modeling, and vehicle-level simulation provides new insights into the practical feasibility of Al-air systems and identifies key design and operational parameters governing their performance. The use of industrially relevant prototype systems further enhances the applicability of the research and bridges the gap between laboratory studies and real-world implementation. This work demonstrates that Al-air batteries, supported by optimized electrolyte conditions, predictive corrosion modeling, and intelligent system integration, represent a viable pathway for next-generation energy storage and EV range extension, while advancing both scientific understanding and practical development.
Autonomous Driving System Rule Learning Using Expert-Defined Causality
(University of Waterloo, 2026-06-10) Bouchard, Frédéric
An increasing number of road users are travelling freely in urban environments. Each of them has their own motion preferences but is expected to comply with the traffic laws. To cope with the motion discrepancies, autonomous vehicles require highly sophisticated reactive decision-making that can adapt their motion given the surrounding environment and the applicable traffic laws. Such decision-makers must be trustworthy, since each mistake can lead to a fatality, and performant, since they must estimate, at a high frequency, which behaviour to implement. This thesis describes how such functionality can be achieved with a practical rule engine learned from expert driving decisions and a precise notion of requirements. We first demonstrate the feasibility of planning the motion of an autonomous vehicle by implementing a prototype that, given a curated training suite of driving examples, can create and maintain a two-layer rule-based theory. Assuming perfect perception, we then design a method that learns the rules based on a precise notion of requirements. An expert anticipates that the decision-maker can enter a state for which a requirement is unmet and therefore specifies with a set of template rules the cause of each anticipated violation. For each template rule, its antecedent entails a notion of causality, and its consequent specifies the behaviour to implement. The set of template rules are used as a labelling function. Namely, each time the decision-maker fails to satisfy a requirement, an associated template rule is used to address the misbehaviour. The rules of the rule-based theory are based on templates. The antecedent of such rules are automatically learned and may have been significantly altered to include new relevant constraints that are expected to cope better with the requirements. Finally, considering that autonomous vehicles rely on sensor capabilities, we thereafter extend our method to compete in the Carla Leaderboard operational design domain. Using the same computer vision as the best performer for which there is code available, we demonstrate that our system can learn a policy that is explainable while performing better than our competitor on the set of provided requirements. This thesis has been divided into three phases, each of which strongly correlates with a paper submitted to a conference or journal for publication. In the first phase, we assess the feasibility of the proposed rule-based architecture by implementing/deploying a rule engine prototype in a level-3 autonomous vehicle driving for 110 kilometres of field tests in an urban environment of the city of Waterloo. Namely, the prototype has an algorithm to create and iteratively refine a rule-based behaviour planner, using a two-layer rule-based theory. The first layer determines a set of feasible parametrized behaviours, given the perceived state of the environment. From these, a resolution function chooses the most conservative high-level maneuver. The second layer then reconciles the parameters into a single behaviour. Based on the set of traffic rules described in a driver handbook, an expert produces a set of training examples expressing the relevant change of behaviours. The algorithm presented in that paper performs hierarchical rule-based machine learning. In the second phase, we formalize the construction of the training suite of driving examples that inevitably comes with the iterative development of the autonomous driving technology infrastructure of software and hardware. Namely, we explore how to extract knowledge from counterexamples encountered while driving in a city generated by the CARLA simulator. For that, we convert the requirements of the CARLA Autonomous Driving Leaderboard into a specification that is used to learn a rule-based policy. We assess the generalization of the learned rule-based policy by evaluating its performance on an unseen city generated by the same simulator. We then compare our performance with InterFuser, a state-of-the-art competing approach, and demonstrate that our method outperforms their method. In the third phase, we use the computer vision and tracker of InterFuser and create our own path generator inspired by the route planner of TransFuser to demonstrate that our method can cope with sensor noise while achieving state-of-the-art performance. In this phase, we use the six official towns that form the CARLA Autonomous Driving Leaderboard as the training towns and attempt to generalize to two unseen towns. Although our initial goal was to become an entry on the CARLA Autonomous Driving Leaderboard, the evaluation infrastructure has become unavailable. Therefore, to be convincing that our approach achieves state-of-the-art performance, we create our own challenge by randomly generating novel routes both on the six official towns and two additional unseen towns that have been released by the same officials. Although we demonstrate that our method outperforms a state-of-the-art end-to-end approach, we list in Limitations a number of issues that have not yet been addressed and constitute limitations to the results presented in this thesis. Thereafter, we speculate on how our method can be extended to mitigate some of these limitations.
Exploring Structure, Agency and Equity in Cross-Sector Partnerships for Advancing Sustainability and Climate Goals
(University of Waterloo, 2026-06-10) Samuel, Naima
The Sustainable Development Goals (SDGs) position partnerships as a central mechanism for advancing sustainability objectives by enabling coordinated efforts across multiple actors and sectors, particularly in addressing complex challenges like climate change. Despite the prominence of partnerships, there remains limited understanding of how cross-sector partnerships function in practice, particularly in local contexts where implementation occurs across municipal, community, and private-sector actors. Existing research has often emphasized formal structures, early phases of collaboration, or normative commitments, providing relatively limited insight into how partnerships are enacted during implementation, how they deliver outcomes, and how equity is embedded and sustained over time. Organized as a three-paper thesis, this dissertation combines a systematic review of sustainability partnerships situated within the SDGs with a comparative qualitative analysis of twelve Canadian local climate action partnerships to examine how cross-sector partnerships are structured, enacted, and adapted, and how effectiveness and equity emerge through the interaction of partnership structures and partner agency. Drawing on document analysis and semi-structured interviews, the analysis is informed by structuration theory, which provides a lens for examining how structures enable and constrain action and how partners reproduce or adapt these arrangements through practice. The findings show that the effectiveness of cross-sector partnerships in local climate action depends on more than formal design alone. Outcomes are shaped through the interaction of partnership structures and partner agency, as structural arrangements influence coordination, participation, and resource allocation while partners interpret, enact, and adapt these arrangements over time. Equity is similarly shaped through these dynamics, not through representational diversity or stated commitments alone, but through deliberate adjustments to decision-making, engagement, and resourcing structures. Co-design emerges as a central practice through which partners collectively reshape partnership arrangements and sustain equity over time. The dissertation contributes an integrated understanding of how cross-sector partnerships support effective and equitable action toward sustainability goals, using local climate mitigation as a site of implementation within the broader sustainability agenda. It extends structuration theory by showing how structure–agency dynamics are enacted through collective practice in multi-actor implementation contexts, highlighting the role of co-design, the influence of partnership arrangements and lifecycle dynamics, and the importance of aligning structures and agency to support both effectiveness and equity. It also offers practical insights for understanding, designing, and adapting partnerships to better support coordinated, inclusive, and effective local climate action.
Effect of Construction Contaminants on the Bond-Slip Behaviour of GFRP Reinforcing Bars
(University of Waterloo, 2026-06-10) Deng, Quanxiang
Glass fibre-reinforced polymer (GFRP) reinforcing bars are an attractive alternative to conventional steel bars in reinforced concrete (RC) bridge construction due to their non-corrosive properties. With advances in production and quality control, GFRP reinforcing bars are an economical alternative for steel reinforcement in many bridge components, particularly in the substructure and at joints. However, gaps remain in the design and construction of GFRP reinforced concrete. including the impact of surface contamination on GFRP reinforcing bars. During construction, construction activities are frequently carried out in close vicinity to exposed GFRP reinforcing bars, which can damage and contaminate their surface. Existing standards, such as CSA S807 and CSA S806, do not provide guidance on how contamination affects performance or how to treat contaminated GFRP reinforcing bars. In Ontario, exposed GFRP reinforcement contaminated by concrete splatter is required to be replaced, leading to costly delays and waste. This study evaluates the impact of surface contamination on GFRP bond behaviour using pullout specimens. 13M and 20M ribbed GFRP bars, and 12M and 20M sand-coated GFRP bars were tested with surface contamination from two common materials used in concrete placement: form oil and concrete splatter. Additionally, non-destructive inspection methods are used to investigate potential differences in ultrasonic pulse velocities associated with different surface contaminants and corresponding bond strength outcomes, and to establish the potential correlation between the contamination effects identified in the pullout and tests those obtained from the non-destructive testing measurements. The results demonstrated that the form oil contamination reduced bond strength and UPV considerably. This suggests that UPV is an effective method for predicting bond loss caused by the form oil contamination. Nevertheless, the concrete splatter contamination exhibited no clear correlations between the pullout test and the Ultrasonic test. Therefore, preventive measures should be applied for the form oil contamination from GFRP reinforcement, and immediate removal is required if detected. Concrete splatter contamination should be removed as a precautionary measure. Furthermore, comparison to the test data showed that the mBPE model yielded a slightly conservative estimate of experimental bond behaviour, while the CMR model tended to under-predict the bond slip response. The experimental bond stresses exceeded the ACI 440 and CSA S806 predictions for all bar sizes and contamination groups.
Parcel-Level Land Valuation under Planning Policy Change: A Spatially Based and Segmented Modeling Framework
(University of Waterloo, 2026-06-10) Wu, Zekai
Planning policies shape land markets by defining development rights, regulating land use intensity, and signaling future growth expectations. However, in current practice, land and parcel value estimation remains highly dependent on expert judgment and manual comparison of recent transactions. While professional appraisal methods are effective for individual assessments, they rely heavily on subjective interpretation and lack systematic mechanisms to identify how planning policy changes influence parcel values across large datasets. This limitation is particularly evident in growing suburban municipalities, where frequent policy updates are used to respond to development pressure and evolving growth objectives. As a result, both municipal decision-making and real estate analysis increasingly require data-driven models capable of automatically evaluating the valuation impacts of planning policy changes. This thesis addresses this gap by developing a spatially explicit, data-driven framework to examine how planning policy changes are capitalized into parcel-level land values in the Town of Aurora, Ontario. The research integrates GIS-based spatial analysis with segmented regression and machine learning modeling to move beyond manual valuation approaches. Parcel-level datasets are constructed by combining transaction records with Official Plan designations, zoning regulations, and adjacent based spatial variables. Parcels are further segmented by size into two datasets to distinguish between house driven and land driven valuation mechanisms, enabling the model to identify the conditions under which planning signals emerge in observed prices.
Multi‑Frequency (X‑, C‑, and L‑Band) F‑SAR Analysis of Scattering Behavior of Freshwater Ice on Noell Lake, Northwest Territories
(University of Waterloo, 2026-06-10) Kharoud, Sukhdip
Lake ice plays a critical role in Arctic and sub-Arctic environments, influencing physical processes within lake systems while also supporting a range of socio-economic activities in northern communities. However, despite its importance, the interaction between lake ice and microwave signals remains inadequately understood, particularly in terms of backscatter behavior during the simultaneous acquisition of active microwave wavelengths. This study utilizes the fully polarimetric FSAR (Flexible Synthetic Aperture Radar) system developed by the Deutsches Zentrum für Luft- und Raumfahrt (DLR), which simultaneously acquired repeat-pass imagery at C-, X-, and L-bands over Noell Lake in the Northwest Territories to investigate the dominant scattering mechanisms associated with lake ice. The results of this study indicate that single-bounce scattering is the dominant scattering mechanism over Noell Lake at all frequencies, but with variable intensities proportional to the wavelength. Furthermore, the influence of tubular bubbles is observed in X- and C-bands but is not detectable in the L-band, aligning with recent research suggesting that tubular bubbles do not significantly increase backscatter, but influence the roughness at the ice-water interface, and is therefore wavelength dependent. These coincident observations at X-, C-, and L-bands improve the understanding of microwave interactions with freshwater ice and the role of ice structural variability in influencing wavelength-dependent scattering responses. Additionally, the investigation of ice property retrieval provides a theoretical foundation for future SAR missions, including support for the NASA–ISRO (NISAR) and TanDEM-L L-band sensors.
Long-term Durability of Iron-based Shape Memory Alloys (Fe-SMAs) and their Performance in Structural Strengthening Applications
(University of Waterloo, 2026-06-09) Carofilis, Wilson
A wide range of repair and strengthening techniques have been developed to address vulnerabilities in aging civil infrastructure. Nevertheless, most conventional approaches rely on passive mechanisms that contribute resistance only when external demands are applied. Active retrofitting strategies, by contrast, introduce permanent restorative forces, such as prestressing, that proactively enhance structural performance, reducing damage accumulation and extending service life. Shape memory alloys (SMAs) offer a unique advantage in this context due to their heat-activated shape memory effect, which enables prestressing without bulky equipment or invasive procedures. Among them, iron-based shape memory alloys (Fe-SMAs) have emerged as a cost-effective and promising solution for structural applications. Despite their growing implementation, the long-term durability and sustained mechanical performance of activated Fe-SMAs remain insufficiently understood, limiting their reliable implementation under environmental exposure and repeated loading. This thesis addresses this critical gap through an integrated experimental–numerical investigation of the durability, fatigue behaviour, and seismic retrofit applications of activated Fe-SMA systems. The experimental program quantifies the evolution of mechanical and functional properties under corrosion and repeated loading. Accelerated durability tests were conducted on activated Fe-SMA dogbone specimens exposed to a sodium chloride solution for varying durations to characterize corrosion induced degradation. Likewise, fatigue tests were performed on pre-cracked reinforced concrete (RC) beams strengthened with Fe-SMA strips to evaluate structural-level performance and service-life implications under cyclic loading. Complementing the experimental work, the numerical investigation evaluates an innovative SMA– based seismic retrofitting strategy. Advanced nonlinear static and dynamic time-history analyses were utilized to quantify global seismic response, identify governing SMA material parameters for retrofit design, and determine critical structural demand parameters influencing performance. Additionally, a resilience-based assessment framework incorporating post-earthquake recovery time was implemented to extend evaluation beyond conventional seismic demand metrics toward functional performance. Experimental results demonstrate that activated Fe-SMAs experience progressive reductions in recovery stress, ultimate tensile strength, and deformation capacity as corrosion develops, while retaining reactivation capability at reduced prestress levels. At the structural scale, RC beams strengthened with Fe-SMA exhibit enhanced fatigue resistance, characterized by reduced crack growth, lower deflections, and decreased of steel reinforcement and concrete strain accumulation. Numerical simulations indicate that the proposed retrofit strategy significantly reduces lateral displacements and residual deformations under seismic loading, although potential increases in floor accelerations highlight important design considerations for non-structural components and functional recovery. Overall, this research establishes a multi-scale understanding of activated Fe-SMA performance by explicitly linking material degradation, structural fatigue behaviour, and system-level seismic response. The findings provide new experimental evidence on long-term durability, performance, structural validation under repeated loading, and application-oriented SMA-based retrofit solutions evaluated through resilience metrics. Together, these contributions support the development of more reliable, durable, and resilient active retrofitting strategies for strengthening deficient and seismically vulnerable infrastructure.
Spatial-Temporal Computer Vision Methods for Automated Vision-Based Visual Inspection
(University of Waterloo, 2026-06-08) Midwinter, Max Xuhao Xue
The objective of this thesis is to investigate how spatial and temporal context can be leveraged to enhance automated vision-based visual inspection (AVVI). The prevailing paradigm in AVVI is the single-shot supervised deep semantic inference model, where an image is processed independently and the resulting semantic prediction is compared against labeled data to generate a supervision signal. While these methods have demonstrated strong performance for defect detection tasks, they often neglect the spatial and temporal context in which inspection data are collected. In practice, engineers rarely make decisions based on a single observation in isolation; instead, they rely on contextual information such as multiple viewpoints of a region of interest, geometric cues for estimating defect scale, and comparisons with previous inspection records. This thesis therefore explores how contextual information inherent in inspection workflows can be incorporated directly into the inference process. Three research challenges are investigated in my thesis: leveraging multi-view imagery to improve defect segmentation, developing and evaluating spatial inference models for defect quantification in civil infrastructure, and enabling visual change detection between unordered sets of inspection data. In Chapter 3, multi-view spatial relationships between inspection images are used to refine segmentations from an unsupervised feature-clustering semantic segmentation model through a novel iterative stochastic consensus algorithm. In Chapter 4, a civil infrastructure RGB-D dataset is created using a custom handheld Light Detection and Ranging scanner, consisting of five short- to medium-span overpass bridges used to benchmark monocular metric depth estimation methods for defect measurement. In Chapter 5, synchronized pairs of novel view synthesis models are constructed to generate pixel-aligned renders of the same structure across inspection events, enabling visual change detection. Finally, Chapter 6 discusses the implications of this research for industrial inspection workflows and possible directions for future work.
From Mock Environments to Ownership-Aware Compilation: Practical Advances in Low-Level Program Reasoning
(University of Waterloo, 2026-06-08) Priya, Siddharth
Automated reasoning can improve both the correctness and the performance of systems software. In practice, however, such reasoning matters only when it fits how developers build software and when it scales to realistic codebases. In verification, one workflow challenge is that the cost of modeling the surrounding environment can exceed the cost of verifying the system itself. Another practical difficulty is scaling precise low-level reasoning and optimization to larger bodies of code. To address these problems, this work develops verification and optimization tools built over a low-level intermediate representation, LLVM-IR, integrating directly with existing compiler toolchains. The thesis first addresses developer workflow friction in verification. vMocks introduces testing-style mocks to code-level formal verification, bringing a familiar testing idiom for specifying environments to a setting where environment modeling is a significant barrier. Instead of building full environment models, developers specify unit-local behavior through SeaMock, a compile-time C++ library compatible with symbolic execution. On the Android Trusty TEE communication layer and the mbedTLS cryptographic library, this approach substantially reduces unit-proof development effort relative to full environment models. The verify-rust case study extends this workflow-oriented perspective to mixed safe–unsafe Rust programs, where the type system alone cannot enforce whole-program properties such as panic freedom and memory safety. This case study builds on SEABMC, a bit-precise bounded model checker for LLVM-IR introduced in prior work. Because SEABMC operates on LLVM-IR, it verifies these properties directly on the bitcode that the Rust compiler already produces. This lets the approach fit into existing Rust toolchains used in production without requiring a custom frontend. The thesis then addresses scale by preserving and exploiting ownership semantics in low-level reasoning and optimization. Cache-at-Pointer and SeaUrchin show that ownership information from high-level languages can remain useful after lowering to low-level representations. Cache-at-Pointer develops ownership semantics for an LLVM-like IR. It then uses a pointer cache to simplify low-level memory reasoning by modeling some memory accesses directly at the pointer rather than through a shared address space. SeaUrchin maps Rust’s ownership discipline to LLVM-IR, preserving semantic structure that is normally discarded during compilation and making it available to optimization. As a case study, ownership-aware loop-invariant code motion shows that the preserved ownership information improves LICM efficacy on realistic Rust benchmarks. Together, these two phases form a single arc: low-level automated reasoning becomes more useful when it better fits developer workflows and when it preserves enough semantic structure to scale. The thesis therefore advances formal verification and compilation not as isolated techniques, but as parts of software engineering practice.
Architecture, Capitalism, and Social Good
(University of Waterloo, 2026-06-05) Mahvash, Kourosh
This study aims to critically investigate the extent of meaningful contributions to social good through architecture given the political economic context within which it operates. It examines the capacity of architecture as a profession as well as the agency and ability of architects as individuals to make such contributions under the capitalist relations of producing space. These relations are defined within a theoretical framework comprised of four core concepts. Gramsci’s theory of hegemony, the notion of urbanization under capitalism, and Lefebvre’s concepts of the “lived space” and “the Right to the City” are the four theoretical foundations which along with a historical examination of the relationship between architecture and capitalism help the research establish its own four central organizing concepts of Agency, Aesthetics, Governance, and Activist Architecture. These four concepts are then used to form a thematic schema for research design. Adopting semi-structured interviews as the instrument of implementing its qualitative method, the process included the recruitment of thirty-six participants - thirty licensed architects based in Toronto, Canada and six key informants who are closely associated and intimately familiar with architecture. The participants’ responses were first subject to deductive thematic analysis before being further discussed and dissected using ‘suspicious interpretation’ method. The results illustrate the limited extent of contributions by architecture and architects to social good while revealing several paths to maximize such contributions within those limits. Architecture may not have a leading or central role in moving towards meaningful social reforms. Nonetheless, it could make meaningful contributions within its own domain of influence by adopting a purposeful social agenda, prioritizing social good over profit in its practices, distancing itself from exploitative labour processes within both creative and construction processes, reclaiming its political capacity, empowering end-users by allowing their active participation in the design process, and replacing entrenched professional privilege, elitism, and egoism with humility. This would allow architecture to contribute its fair share to the struggles for a socially, economically, and politically just future.
Super-Queeros: Transformations of Queer Feminist Representation in the DC Pride Comics Run 2021-2025
(University of Waterloo, 2026-06-05) Grafton, Laura
This thesis analyzes the narrative and visual strategies used in DC Comics’ DC Pride anthology series from 2021 to 2025, examining how these texts construct and evolve a “model Super-Queero” across this time period. Drawing on visual rhetoric, semiotics, narratology, and queer and feminist theory, this project argues that the DC Pride run does not simply represent queer identity, but actively produces a shifting model of acceptable queerness that reflects broader sociopolitical conditions in the United States (USA). Across the five-year run, I argue that the anthology moves from an emphasis on visibility, celebration, and reader identification toward increasing normalization, containment, and disidentification. Early issues position queer characters as sites of pride, and community, using visual and narrative techniques that invite readers, particularly queer readers, into processes of identification. However, as the series progresses, these same formal elements are reoriented to privilege legibility, safety, and social acceptance, encouraging distance from more disruptive or visibly queer expressions of identity. Through close analysis of recurring formal patterns and focused case studies of the DC Pride issues covers, opening stories, and the #Harlivy stories in the issues, this thesis demonstrates how mainstream comic media negotiates the boundaries of queer representation. While these characters have the potential to expand dominant models of queerness, their depiction within the DC Pride run often reinscribes normative expectations through stylistic containment and narrative framing. Overall, I argue that the model Super-Queero constructed across the anthologies reflects a broader cultural shift toward regulating queer visibility, highlighting the role of popular media in shaping not only how queerness is represented, but how it is understood, performed, and then made (un)acceptable within contemporary culture.
Vector bundles on toric stacks
(University of Waterloo, 2026-06-04) Singh, Yash Vardhan
This thesis is concerned with a generalization of Klyachko's classification of toric vector bundles to toric stacks. The work of Klyachko gave an elegant method of studying toric vector bundles through filtrations of a vector space. We extend these techniques to vector bundles on a toric stack and generalize the aspects of Klyachko's work to a more geometric setting. In particular, we show that the category of reflexive sheaves on a toric stack is equivalent to a category of filtered reflexives sheaves of its largest Deligne-Mumford substack. We then combine this with an equivariant version of Gubeladze's result on the splitting of vector bundles on toric varieties to prove a classification theorem for vector bundles on toric stacks. As an application we reprove a known result on the splitting of rank-$2$ bundles on $[\bP^n/\bG_m]$ for a particular $\bG_m$ action. Our methods involve an extension of Cox's construction of homogeneous coordinates to toric stacks and we incorporate ideas from the classical Rees construction. We also study the Chow ring of toric stacks, and give a presentation of the Chow ring of a smooth toric stack.
Information Extraction for Low-Resource Schemas
(University of Waterloo, 2026-06-04) Xu, Justin
Information Extraction (IE) is a set of important tasks in the study of creating structured data such as knowledge graphs from unstructured data such as text. The past paradigm of IE focused on models with specialized neural network architectures, usually based on transformer encoders. These models typically focus on a single subtask of IE, following a single schema of entity and relation types, and are trained via supervised learning on large datasets of annotated texts. Meanwhile, the current paradigm of IE, called Universal IE (UIE), involves large language models which can generalize across IE subtasks and to completely unseen schemas, but which lack other abilities such as entity grounding and calibration. We first discuss structural consistency, a new measure of robustness in information extraction based on compositionality. We present structural consistency post-training (SCPT) as a data augmentation method to boost structural consistency for a wide range of model architectures. Besides greatly improving robustness, SCPT significantly reduces the amount of labelled data needed to achieve the same level of performance when training specialized IE models. Second, we use reasoning-based data augmentation techniques to gather AdaIE, a very large collection of human-annotated information extraction schemas. We diverge from UIE and align the dataset with a new task we call Guided Information Extraction (GIE). GIE emphasizes the tight grounding and schema-following requirements which have been largely neglected in UIE. Evaluations of state-of-the-art UIE models reveal that state of the art UIE methods can be surpassed by recent commercial large language models (LLMs). Although those LLMs achieve below human performance on AdaIE, they are rapidly advancing. Overall, we hope that both works presented will steer the IE research community towards unifying the strengths of the old and new IE paradigms, while casting light on their weaknesses.

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