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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Assessment of ERA5-Land Lake Ice Related Variables from Satellite Observations
(University of Waterloo, 2025-12-19) Mansingh, Ariana
Lake ice is an important climatic indicator because it responds to and alters surface energy fluxes, which in turn influence weather and climate (e.g., precipitation, air temperature). Therefore, accurately representing lake-atmosphere interactions within climate and weather models has been shown to reduce forecast errors. Despite the recognized importance of lake ice processes within models, few studies have evaluated the quality of the lake ice-related variables available from ERA5-Land, a widely used reanalysis product. To address this gap, this thesis evaluates ERA5-Land’s lake ice estimates against satellite-derived observations from NOAA, CIS, IMS and MODIS. It assesses biases in lake ice fraction, timing and surface temperature across seven Canadian lakes over 20 years (2004-2023). The study lakes are grouped into northern lakes (Great Bear, Great Slave, Athabasca and Winnipeg) and the Laurentian Great Lakes (Superior, Huron and Erie). The biases were quantified using mean bias error (MBE) and mean absolute error (MAE), with ERA5-Land treated as “predicted” values and satellite-derived products as “observed” values. This thesis provides one of the first spatial and temporally extensive evaluations of ERA5-Land’s lake ice estimates. The overall findings show that ERA5-Land consistently overestimated lake ice fraction during freeze-up and break-up. Across all lakes, ERA5-Land generally produced earlier freeze-up timing, earlier break-up start, and later break-up end than observations. While timing bias followed similar patterns across lakes, distinct patterns emerged between the northern lakes and the Laurentian Great Lakes. These patterns indicate broader weaknesses of ERA5-Land, which uses the Freshwater Lake model (FLake) as its lake parameterization scheme, notably the omission of snow cover over lake ice and the tendency of the product to form a full ice cover on the Laurentian Great Lakes, which typically experience 40-80% ice fraction at winter maximum. As a result, high MAE was observed during both freeze-up (max=47%) and break-up (max=62%). Consequently, this overestimation of ice cover in ERA5-Land typically led to a daytime cold bias in surface temperatures during the ice-covered period. Additionally, it contributed to ice timing biases, notably the freeze-up end (~22 days earlier on average) and the break-up start (~25-28 days later on average). The lack of consideration of snow cover on ice in FLake/ERA5-Land prevents accounting for its effects on ice growth, heat absorption, and surface temperature. It is well known that snow slows ice growth by reducing downward heat transfer. Thus, ERA5-Land overestimates lake ice thickness across all lakes, which in turn contributes to the delay in break-up start. The early break-up end timing is likely linked to ERA5-Land neglecting the cooling effect of snow’s high albedo, which would otherwise slow melt by reflecting solar radiation. Additionally, during months of high snowfall, ERA5-Land produced a larger warm surface temperature bias, most notable among the northern lakes. Overall, this thesis quantified the biases arising from two notable weaknesses in ERA5-Land’s parameterization: the omission of snow cover on ice and the inability to account for partial ice coverage in the large lakes examined in this research. The quantification of biases provides insight into how these weaknesses skew ERA5-Land estimates. This thesis provides new insights into the limitations of ERA5-Land regarding lake ice, which should be considered leading to for future product releases.
Love, Resilience, and the Past: The Role of Positive Emotion Regulation in Overcoming Childhood Maltreatment and Building Strong Romantic Relationships
(University of Waterloo, 2025-12-19) McNeil, Julia
Experiences of childhood maltreatment (CM) are associated with relationship and sexual difficulties in adulthood (Vaillancourt-Morel, et al., 2024). Research has shown that these issues are partially explained by difficulties regulating negative emotions (DiLillo et al., 2009). However, the effect CM has on the regulation of positive emotions has received considerably less attention. In this thesis I examined how CM is related to fear of positive and negative emotional states (Studies 1-3), using online-self report questionnaires, I tested if this anxiety mediates the association between CM and difficulties in relationships (Studies 2 & 3), and finally, I examined how CM is related to an individuals’ ability to regulate their positive and negative emotions in response to images that evoke positive and negative emotions. My results consistently showed that CM is related to fear of positive and negative emotional states (Studies 1-3). Consistently I found an association between the intensity of CM experienced and decreased satisfaction with communication in adult long-term relationships (Studies 2 & 3). This association was mediated by fear of emotions (Study 2), with Study 3 showing unique effects for both fear of positive and negative emotions. Finally, my results showed that CM was associated with difficulty enhancing positive emotions and improved performance when asked to decrease positive emotions (Study 3). These results provide evidence that CM affects individuals’ ability to tolerate and regulate their positive emotions. Furthermore, my results suggest that difficulties with positive emotions play a role in long-term relationship difficulties reported by survivors of CM. The present research suggests that clinicians should focus on improving tolerance for positive emotions and teaching tools for capitalizing on positive experiences when working with survivors of CM.
Revivifying, Repurposing, Reimagining: From Commodification to Kinship in 21st-Century De-Extinction and Xenotransplantation Narratives
(University of Waterloo, 2025-12-19) Sanderson, Jerika
De-extinction and xenotransplantation represent two key 21st-century biotechnological developments, both of which aim to use genetic engineering to address ecological and medical crises. This dissertation investigates the representation of de-extinction and xenotransplantation by scientific corporations, in the media, and in fiction. In particular, I draw on critical posthumanist theory to investigate how techno-optimistic and transhumanist rhetoric has influenced de-extinction and xenotransplantation narratives; how narratives respond to key issues in bioethics and environmental ethics; the implications that these narratives suggest for how biotechnology is shaping human and nonhuman identity; and the way that they explore possibilities for multispecies care, kinship, and entanglement. My analysis in Part I shows that de-extinction is frequently framed in terms of the biomedical and human health benefits that it can offer. While this biomedical framing is reflected in the Jurassic World films (2015, 2018, 2022) and the novels Ghost Species (2020) and The Neanderthal’s Aunt (2014), these narratives focus on the risks arising from the exploitation and commodification of genetic material. In my analysis of xenotransplantation narratives in Part II, I observed that pigs are frequently framed as an abundant supply of organs that can solve the organ shortage crisis. In contrast, the novel Pig-Heart Boy (1997) and the film We Ate the Children Last (2011) focus on the bioethical risks faced by the first patients to undergo xenotransplantation, such as their vulnerability and the risk of discrimination, while the novels Oryx and Crake (2003) and Chromosome 6 (1998) counter the frame of abundance by depicting the potential for detrimental environmental, political, and economic impacts. Lastly, my analysis in Part III of the short story “The Birdsong Fossil” (2021) and the novel Pighearted (2021) reveals that these narratives prioritize care, kinship, and entanglement, providing possibilities for reimagining the animals created by biotechnology beyond the hype of charismatic megafauna and the spare parts metaphor in de-extinction and xenotransplantation discourse. By drawing on multispecies environmental ethics and posthumanist bioethics, I conclude that these narratives can allow us to envision more ethical applications of biotechnology, which can thereby shape the future of de-extinction and xenotransplantation.
Challenges and Opportunities for Sustainable Nitrogen Management in Dairy Systems
(University of Waterloo, 2025-12-19) Lakhanpal, Garima
Nitrogen (N) is central to agricultural productivity, yet its mismanagement drives water and air pollution across the world. Ireland’s grass-based dairy systems are among the most N-intensive in the European Union (EU), with high inorganic and organic fertilizer sustaining productivity but creating persistent surpluses that threaten groundwater and surface water quality. Despite major policy efforts, Ireland continues to struggle to meet EU Water Framework Directive (WFD) chemical targets for good water status. However, Ireland is still seeking the renewal of its Nitrates Derogation, which allows exceptionally high stocking rates up to 220 kg N ha⁻¹ yr⁻¹. This tension between economic needs and environmental compliance defines one of the country’s greatest agri-environmental challenges. The EU is moving toward tighter nutrient limits and nature restoration objectives, making it essential to understand whether sustainable dairy production can coexist with future regulatory expectations. One of the main obstacles to achieving water-quality goals is the temporal disconnect between management interventions and measurable improvements, which can erode stakeholder confidence and obscure the true impact of mitigation policies. In Ireland, the EU WFD program of measures (PoMs) is carried out under the Nitrates Directive, which include nutrient management, land management and farmyard management strategies to protect water quality. These lags are increasingly attributed to legacy N i.e., reactive N accumulated in soils and subsoils from past surpluses that continue to leach long after inputs decline. While groundwater legacy effects are recognized (i.e., the time it takes water to travel through the soil termed hydrologic time lag), few studies worldwide have directly quantified soil legacy N (i.e., biogeochemical time lags), and none had done so in Ireland prior to this research. Understanding the scale, distribution, and persistence of these soil pools is critical for designing realistic mitigation timelines and adaptive policies. The overarching aim of my research was therefore to assess N dynamics and environmental outcomes in Irish dairy systems by evaluating mitigation scenarios and quantifying legacy soil N accumulation to understand how current and historical management, drainage class, and hydrogeological setting influence both near-term losses and the pace of environmental recovery. I combined process-based modelling, multi-decadal farm data, deep soil coring, and groundwater monitoring to connect farm management decisions with both short- and long-term system responses. Together, these studies form the first integrated assessment of soil N legacies in Irish dairy systems. In Chapter 2, I used the €riN-MDSM model to simulate N flows, surpluses, and losses in a well-drained dairy farm operating under derogation conditions. This model, developed to represent N cycling in Irish grass-based systems, quantifies losses of nitrate (NO₃⁻), ammonia (NH₃), nitrous oxide (N₂O), and dinitrogen (N₂) from urine, dung, slurry, dairy soiled water, and fertilizer. I simulated a range of management scenarios, including reduced inorganic N rates (200–225 kg N ha⁻¹) and organic rates (170–430 kg N ha⁻¹), substitution of calcium ammonium nitrate (CAN) with protected urea, and restrictive grazing during vulnerable winter–spring months. Results showed that integrated approaches combining restrictive grazing, protected urea, and reduced fertilizer inputs lowered NO₃⁻ leaching by up to 44 % and NH₃ volatilization by 31 %, bringing water losses close to the 30 kg N ha⁻¹ threshold for good groundwater quality. These findings demonstrated that substantial environmental gains are possible through system-level optimization, but that even under improved management, N surpluses remain high, implying persistent risks to water and air quality. This modelling work provided a critical benchmark for assessing what levels of mitigation might be achievable within the derogation framework and highlighted the need to understand how historical surpluses continue to affect recovery, setting the stage for the legacy N analyses that followed in the next phase of this research study. In Chapter 3, I conducted a 24-year investigation (2001–2024) at Moorepark Teagasc Research Farm (known as Curtins Research Farm locally) in southern Ireland, a well-drained, karstic site with low denitrification potential. I reconstructed multi-decadal N budgets from detailed farm records and collected 75 soil cores across 15 paddocks, 1m deep profiles representing a gradient of historical management intensity. Annual N surpluses frequently exceeded 200 kg N ha⁻¹ yr⁻¹, leading to cumulative soil N accumulation of 4,000–5,500 kg N ha⁻¹ in the top 50 cm. Groundwater NO₃⁻ loads declined from over 70 kg N ha⁻¹ in the early 2000s to under 30 kg N ha⁻¹ by 2024, yet concentrations have plateaued rather than continuing to fall. This persistent signal alludes that subsoil N stored from past decades continues to mineralize and leach, sustaining groundwater nitrate levels despite reduced inputs. These findings provide the first direct quantification of legacy soil N in Irish dairy systems, showing that deep soil stores act as long-term sources of reactive N, constraining the pace of water quality recovery even when surface management improves. In Chapter 4, I expanded the investigation to include the Johnstown Castle Teagasc Dairy Research Farm, a variably drained site in the southeast with finer-textured soils and higher denitrification potential. I analyzed 45 soil cores from 9 paddocks, 1 m deep profiles covering an 18-year management period and compared results to those from Curtins. Despite lower annual surpluses (~100–150 kg N ha⁻¹ yr⁻¹), Johnstown Castle soils contained 4,000–11,000 kg N ha⁻¹ in the upper 50 cm, substantially higher than the well-drained Curtins profiles. The difference reflected higher clay and silt content, which enhanced N retention through adsorption and organic-mineral associations, as well as shallower water tables and moderate denitrification that reduced nitrate transport to groundwater but trapped nitrogen in the soil profile. These results revealed a clear trade-off: well-drained systems potentially act as “fast transmitters,” showing rapid leaching but quicker recovery when management improves, whereas variably drained systems are possibly “slow retainers,” buffering groundwater in the short term but accumulating persistent legacy N stores that prolong recovery. By linking long-term management records, soil data, and investigating groundwater trends across these contrasting systems, I demonstrated that N accumulation is governed by the interaction of soil texture, soil drainage class, hydrology, denitrification potential, and historical management intensity. Across both sites, total soil N accumulation exceeded 3,000–11,000 kg N ha⁻¹, far higher than values reported for most temperate cropland systems, confirming the exceptional capacity of Irish grassland soils to store reactive N from decades of intensive management. This thesis makes several novel contributions. It provides the first empirical evidence of soil legacy N magnitudes in temperate dairy grasslands, quantifies their long-term influence on water quality and nitrate dynamics, and develops a conceptual framework concerning drainage, soil texture, and hydrology to N retention and release. It also demonstrates how soil legacy N can be reframed as both a risk and a resource—a potential nutrient reservoir that, if managed strategically, could offset fertilizer needs during the transition to lower-input systems. These findings have direct implications for Ireland’s compliance with the EU Nitrates and WFD. Current six-year reporting cycles are too short to capture recovery in legacy-affected catchments, creating the perception of policy failure. Integrating soil monitoring to 1 m depth alongside existing high-resolution catchment and groundwater networks would enable more accurate assessment of progress and support realistic, site-specific mitigation timelines. Legacy N must be explicitly incorporated into nutrient models, regulatory assessments, and PoMs to ensure that both soil and water systems are managed as coupled components of the nitrogen cycle. Ultimately, this research underscores that Ireland’s path to sustainable dairy production requires addressing both current N surpluses and historical legacies. The methods and evidence developed here — combining modelling, deep soil sampling, and long-term monitoring offer a blueprint for future national assessments and international comparisons. As EU policy evolves toward stricter nutrient limits and nature restoration goals, understanding and managing legacy N will be fundamental to aligning agricultural productivity with environmental resilience.
Exploring intersectoral collaboration in a community-based climate adaptation initiative: A qualitative case study of the Waterloo Region Heat, Cold and Air Quality Network (WRHCAN)
(University of Waterloo, 2025-12-19) Abbas, Sabeen
Background: An increase in the frequency and severity of extreme weather and poor air quality events due to anthropogenic climate change has resulted in negative implications for human and planetary health. Understanding the role of local public health units in the development and implementation of community-based climate change adaptation initiatives can minimize the health impacts of climate change and enhance community resilience. This study aimed to explore the facilitators and barriers to intersectoral collaboration for Network partners of the Waterloo Region Heat, Cold and Air Quality Network (WRHCAN), a public health led climate adaptation initiative. Methods: A community engaged research approach informed the study design and community-academic partnership between the University of Waterloo and Region of Waterloo Public Health (ROWPH). A case study methodology was applied to explore the processes of intersectoral collaboration in the context of the WRHCAN. Data sources included a focus group with ROWPH, 13 semi-structured interviews with Network partners, participant observation of two Network meetings, and a document review of selected WRHCAN internal documents. Recruitment was facilitated by ROWPH, and data collection and analysis were guided by the Bergen Model of Collaborative Functioning, a theoretical framework for intersectoral collaboration. All interviews were audio-recorded using Teams and transcribed verbatim. Interview data were thematically analyzed using a hybrid inductive-deductive approach. Results: Network partners identified several facilitators and barriers, as well as contextual factors influencing intersectoral collaboration in the WRHCAN. For Network partners, facilitators included alignment with WRHCAN objectives, coordination by ROWPH, usefulness of communication products, and information and resource sharing with other Network partners. Barriers included accessibility of information and resources for vulnerable populations, and the need for more tailored training and response by frontline staff. Contextual factors included the housing and affordability crisis impacting Waterloo Region and the need to address the specific challenges of those experiencing substance use challenges, mental health concerns, and/or homelessness. Conclusion: This study highlighted intersectoral collaboration as an approach that can be leveraged by local public health units in the design and implementation of community-based climate change adaptation initiatives. This study provides insights into the facilitators and barriers experienced by WRHCAN Network partners. The findings from this study can inform future climate change adaptation efforts that utilize intersectoral collaboration.
Computer-Aided Modeling and Tuning of RF Acoustic Wave Filters
(University of Waterloo, 2025-12-19) Ou, Matthew
Mobile radios must operate across many frequency bands while sharing antennas and supporting closely spaced transmit and receive paths. Achieving this requires high-performance RF filtering that suppresses interference, limits unwanted emissions, and provides strong isolation. In smartphones, these functions are predominantly realized using acoustic-wave devices, particularly SAW- and BAW-based resonator filters implemented as duplexers and multiplexers. Their high selectivity, low insertion loss, and compact size have displaced conventional solutions as systems expanded from limited third-generation band sets to much larger fifth-generation portfolios. This growth in band count has increased both the number and diversity of filters within a single platform, making acoustic filters a dominant contributor to RF front-end cost and area. This dissertation addresses key challenges in the dynamic tuning of acoustic filters and in late-stage band targeting under process-induced detuning. Several bandwidth-reconfigurable architectures are introduced that integrate switches with resonators to enable bandwidth reconfiguration. In addition, the dissertation demonstrates that strategic modification of interdigital transducer configurations in ladder acoustic filters enables discrete control of the resonator electromechanical coupling coefficient. By adjusting the ratio of positive to negative IDT fingers, coupling can be set to selected levels to improve selectivity and asymmetry and to meet diverse specifications. VO₂-based RF switches are integrated directly with SAW resonators to select discrete IDT states, enabling ladder bandwidth tuning while maintaining low insertion loss. The dissertation further demonstrates a computer-aided tuning framework for late-stage band targeting in acoustic filters. A resonator-level extraction method reconstructs ladder element parameters directly from measured filter responses using stable rational approximation of the driving-point function, pole-zero identification via partial and continued fraction expansions, topology-aligned element matching, and sequential decomposition of series and shunt resonators. In addition, an on-wafer tuning strategy is demonstrated that prescribes minimal, physically realizable corrections without embedded tuning components or manual intervention. The approach spatially programs mass loading through patterned dielectric overlays for additive shifts and electrode thinning or ion milling for subtractive shifts, enabling heterogeneous per-resonator trims simultaneously. Experimental results demonstrate recovery of target passband characteristics, with improved return loss and insertion loss, establishing a practical framework for acoustic-filter correction under manufacturing-induced non-idealities.
Static-to-Kinetic Solutions in Adaptive Reuse: Mechanisms for Transformation
(University of Waterloo, 2025-12-19) Farmer, Theresa
Public library branches stand as vital social infrastructure, yet their physical forms increasingly struggle to keep pace with technological, social, and environmental change. While their programs now support many different modes of making, learning, and gathering, the buildings remain static, limiting adaptability and user agency. Demolition and rebuilding are often treated as the only solutions, but such approaches are financially unsustainable and environmentally destructive, erasing buildings that embody local identity and collective memory. This thesis explores an alternative path: the use of responsive architectural additions that extend existing libraries without compromising their structural integrity or cultural meaning. It argues that preservation today must move beyond maintaining appearance or form toward sustaining continuity through active use and adaptation over time. Building on William Zuk and Roger H. Clark’s theory of kinetic architecture, the research explores a kinetic exhibition scaffold system composed of adjustable floors, walls, and furnishings as a way to achieve responsiveness and enable the public to shape and experience space. The Pleasant View Branch (1975) in Toronto, Canada, serves as the test site. The proposal introduces a lightweight overbuild addition, a new structure that appears to hover above the existing library while remaining structurally independent. This approach allows the original building to remain operational during construction, maintaining community access as transformation occurs above. Together, the elevated addition and reconfigurable interior scaffolding establish a practical model of adaptive reuse, where space can expand, contract, and transform in response to evolving patterns of use. The result is an extendable strategy for renewing the functional, civic, and environmental lifespan of public library branches without sacrificing the histories they hold.
Polyelectrolyte templated synthesis and formation behavior of high entropy alloys
(University of Waterloo, 2025-12-18) Li, Alexander
High entropy alloys have recently received significant attention in electrocatalysis because their unique compositional complexity can enhance both catalytic activity and long term stability. Despite this promise, there remains a lack of scalable synthesis methods that can produce nanoscale high entropy alloys with controlled and more complex morphologies. One promising strategy is to leverage the electrical double layer that forms when polyelectrolytes interact with metal salts. Polyelectrolytes can serve as effective templates by creating a locally high ion concentration along their surface, which promotes initial mixing during nanoparticle nucleation. In particular, polystyrene sulfonate can also bridge nucleating particles, allowing for the formation of more intricate, networked morphologies. The goal of this work is to investigate how polyelectrolyte concentration, polymer chain length, and different reducing agents influence the resulting catalyst composition and morphology. In addition, this study aims to provide insight into the mechanisms of nanoscale high entropy alloy formation.
Robust and Hierarchy-Aware Classification
(University of Waterloo, 2025-12-18) Pellegrino, Nicholas
The BIOSCAN project, led by the International Barcode of Life (iBOL) Consortium, is an international, multi-year, and multidisciplinary effort seeking to catalogue all multicellular life on Earth by 2045 to enable the global-scale study of changes in biodiversity, species interactions, and species dynamics. Access to this information has the potential to inform strategies to mitigate the damaging ecological effects of climate change. In the near term, the goal is to catalogue all insects. Each sample is imaged, genetically barcoded, and taxonomically classified by domain experts, a time- and resource-intensive process that is becoming increasingly impractical as collection rates surpass five million samples annually. Addressing such needs is among the foundational motivations for the research of this thesis. This thesis presents several contributions motivated by the challenges of the BIOSCAN project. Over five million insect samples were organized into a machine-learning-ready dataset, and a deep neural network classifier was developed to establish a baseline for image-to-taxonomy classification performance. To mitigate the harmful impacts of mislabelled samples in training data, a study of neural network architecture robustness was conducted alongside the development of two novel loss functions: Blurry and Piecewise-zero loss. Blurry loss de-weights and reverses the gradient of samples likely to be mislabelled, while Piecewise-zero loss disregards these samples. These improvements strengthen model robustness and enhance label error detection, enabling the referral of suspicious samples for expert review and correction. Additional work investigates the hierarchical structure of biological data and its integration into classification models, specifically through Hyperbolic neural networks, and measures the benefits of doing so in comparison to using conventional architectures. Finally, this thesis explores aligning image, genetic, and taxonomic representations in a hierarchy-aware manner to improve retrieval across modalities. The contributions of this thesis advance the application of machine learning to facilitate the ongoing global-scale cataloguing of insect life. As challenges such as label errors, hierarchical structures in data, and incomplete annotations are present across many domains, the contributions are valuable to both the machine learning community and the global network of BIOSCAN collaborators.
Predicting ACL Injuries Using Machine Learning Models and Tibial Anatomical Predictors
(University of Waterloo, 2025-12-18) Cheng-Hao, Kao
The tibial slope and the tibial depth are well-established risk factors for Anterior Cruciate Ligament (ACL) injury. As ML continues to progress, it has become an increasingly reliable tool for clinical screening and risk factor analysis. This thesis aims to develop and validate an explainable prognostic ML model to predict ACL injury outcomes from these Tibial Anatomical Feature (TAF), and identify the most predictive features among these parameters. A dataset comprising Coronal Tibial Slope (CTS), Medial Tibial Slope (MTS), Lateral Tibial Slope (LTS), Medial Tibial Depth (MTD), and sex was constructed using MRI scans taken from 104 subjects (44 males: 22 injured, 22 uninjured; 60 females: 27 injured, 33 uninjured). Two distinct ML pipelines were developed: a self-developed pipeline (including K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), XGBoost, CATBoost, Multi-Layer Perceptron (MLP), and TabNet) and an advanced AutoGluon pipeline (including XGBoost, LightGBM, CatBoost, TabPFN, TabM, TabICL, MITRA, and their weighted ensembles). Both were designed as end-to-end pipelines to process the dataset and output predictions with integrated feature importance explanations. Empirically, the AutoGluon Pipeline demonstrated superior performance and training-time efficiency. The recommended F2-tuned standard ensemble achieved an F2-score of 0.736 on the validation set. On the test set, it demonstrated a test balanced accuracy of 0.955, F1-score of 0.952, F2-score of 0.980, ROC AUC of 1.000, precision of 0.909, and recall of 1.000. A full-dataset model, the F2-tuned full-dataset ensemble refitted on the entire dataset for clinical deployment achieved a validation F2-score of 0.813. The global feature importance analyses performed via SHapley Additive exPlanations (SHAP), established the descending order of influences as MTD, LTS, MTS, CTS, and sex. In summary, the study recommends two versions of the F2-tuned prognostic models, one being a standard ensemble model and the other a full-dataset ensemble. The former, which demonstrated moderately high predictive power, was designed for subsequent research comparison. The latter, without access to the original held-out test set, is constructed for maximum robustness and generalization in real-life clinical deployment. Global feature importance analyses elucidated from the standard ensemble decreased MTD along with increased LTS and MTS as most contributive features for ACL injury. These models serve as both feature attribution tools as well as clinical screening tools. These models are intended to be integrated into clinical practice as explainable machines to assist clinicians in predicting the likelihood of ACL injury.
Identifying the Relative Contribution of Motoric and Cognitive Engagement on Spatial Memory
(University of Waterloo, 2025-12-18) Sivashankar, Yadurshana
I investigated the cognitive mechanisms underlying spatial memory, with the aim of differentiating the contributions of motor engagement and decision-making. In Experiment 1, I examined whether volitional motor control or decision-making, during initial exploration of a map within virtual reality, better supported retention of routes travelled. Participants explored virtual cities under three navigation conditions that varied in terms of motor and decision-making demands. During Active navigation, participants had volitional control over their movement using hand-held controllers, allowing head and body rotation in a swivel chair, and made independent decisions about which route to take to reach a target location. During Guided navigation, participants still controlled their movement, but followed a visually guided path overlaid onto the road, eliminating the need for decisionmaking. In the Passive condition participants observed a pre-defined route without having to make any decisions or engage motorically. Following exploration of each environment, participants were asked to “re-trace their steps” using the exact route they had just traveled, from the same starting point. Route memory was significantly better following Active and Guided encoding relative to Passive, suggesting that volitional movement during navigation underlay the benefit. Notably, the complexity of the path chosen by participant at encoding did not predict accuracy of route memory. Experiment 2 assessed the necessity of motor engagement and decision-making by comparing memory benefits following two types of VR implementation: Desktop-VR, in which movement was limited to keyboard input (lower motor engagement), and Headset-VR, in which participants navigated using a steering wheel (higher motor engagement). An effect of navigation strategy emerged only in the Headset-VR group: Active and Guided navigation at encoding led to significantly better route memory relative to Passive. No significant differences emerged between Active and Guided trials, suggesting that motoric engagement, rather than decision-making, is the driver of memory performance. Interestingly, in Headset-VR, a stronger personal preference for Active exploration predicted better route memory, whereas in Desktop-VR, personal motivation predicted route memory accuracy. However, neither motivation nor preference mediated performance, indicating that these factors did not account for the effect of navigation condition on memory. If motor engagement contributes to the formation of route memories, as suggested by experiments 1 and 2, then reduced mobility in older adults may influence performance, and the components underlying it. At the same time, reliance on landmark memory to guide memory may be heightened, as landmarks provide salient external cues that could compensate for reduced motor-based encoding. To test these predictions, in Experiment 3 I examined route and landmark memory in younger and older adults as they explored virtual environments. In younger adults, both Active and Guided navigation equally enhanced memory for routes compared to Passive, replicating experiments 1 and 2. However, in older adults only Active navigation, which engaged both movement and decision-making, resulted in improved route memory. Further, landmark memory in older adults benefitted the most from Active relative to Passive and Guided navigation. Simply put, active encoding eliminated age-related deficits in route memory, suggesting that decision-making (present only in this condition) during navigation may be particularly important for supporting spatial memory in aging populations. This benefit may reflect increased recruitment of frontal lobe-based resources during active navigation, which can compensate for reductions in motor engagement. There were some differences in motivation and preference ratings across conditions in both age groups. However, these subjective measures did not emerge as significant predictors of memory performance. Overall, my findings suggest that motor engagement plays a more critical role than decision-making in enhancing subsequent route memory in younger adults, whereas conditions that require decision-making benefit memory in older adults. These findings have important implications for the design of navigational tools and cognitive interventions aimed at promoting spatial independence, particularly among older adults.
Mindful Streets: Examining the politics and practices of everyday mobility negotiated by those who are neurodivergent and the potential for more inclusive (and just) street design for ‘all’
(University of Waterloo, 2025-12-18) Leger, Samantha
Accommodating ‘all abilities’ in the planning and design of streets and transport-spaces has been a longstanding, yet unmet, objective in transportation planning. Although the discipline has been striving to become more inclusive with efforts to plan for ‘complete streets’ that accommodate diverse mode-users of ‘all ages & abilities’, the ways in which different abilities are planned for often remain limited. This is evidenced in cursory and unnuanced considerations that do not engage with the relational lived experiences of getting around whilst dis/abled or differently abled (Stafford et al., 2022). As such, despite objectives to accommodate ‘all’ abilities in complete streets planning paradigms, differential mobilities produced by being differently abled can remain under-considered. This is especially true for people who experience cognitive difference or who are neurodivergent, whose mobility needs are too often not well-articulated and are entirely or nearly absent from inclusivity considerations. The misalignment between the promises and outcomes of planning for complete streets inclusivity promises is representative of a broader tension in the planning and design of transportation, wherein inclusive-transportation paradigms are constrained within wider politics of automobility and rationalist legacies within the transportation planning discipline. In this, for what (and whom) the street functions is contested within an inertia of autocentric values, ideologies, and ways-of-planning that have proven difficult to unsettle. However, the resultant status-quo of flattened and ‘one-size-fits-all’ approaches to accommodating differential abilities cannot be upheld. As of 2022, 8 million people across Canada live with some form of dis/ability. Particularly, many of those people fall within the umbrella of being ‘neurodivergent’, including in developmental, learning, and mental-health dis/abilities. Notably, those with development dis/abilities (including Autism Spectrum Condition) were the most likely to report unmet accommodations needs (70%). Moreover, learning dis/abilities, such as Attention Deficit and Hyperactivity Disorder (ADHD), were the second-most emergent form of dis/ability for youth (after only mental-health dis/abilities) (Statistics Canada, 2024a). In this, there is an evident need for transportation planning to challenge the current ways in which neurodivergence is included within the efforts to plan for ‘all’ abilities; but the question then becomes, how? Utilizing a framework informed by both the neurodiversity paradigm, that reframes neurodivergence not as a deficit but rather part of the full-spectrum of cognitive ability and Mimi Sheller’s Mobility Justice, that situates transportation planning within the politics and production of mobilities across the macro, mesa, and micro-political, the enclosed thesis responds to this gap in a three-fold approach which 1) explores how politics of automobility continue to shape emergent transportation-planning paradigms, 2) engages with the lived-experiences of getting around in everyday travel for people who are neurodivergent (those who identify as either Autistic or with ADHD) and 3) interrogates how such experiences can inform more-inclusive efforts to plan for ‘all abilities’ in transportation. To respond to the objectives, a qualitative research approach was designed based in both critical analysis of complete street planning documents (n=5) and sit-down (n=30) and go-along (n=14) interviews with people who are neurodivergent on their experiences of being-in-travel and navigating everyday-travel spaces. The findings were discussed in three manuscripts enclosed within this thesis. Particularly, the first objective is addressed in manuscript #1, which examines the current politics of complete streets through a critical discourse analysis of current complete street design guidelines sourced from across Ontario. This review allowed for a better understanding of how complete street planning paradigms remain embedded within politics of automobility, and the resistant potential of complete streets to emulate vélomobility. This thus provided insight into how transportation planning both influences and is influenced from the macro-political (or from “above”). Of note, the first manuscript provides the basis in which the second and third manuscript were informed, noting that complete street planning paradigms are not untethered from broader societal power-structures which can then construct (or constrain) inclusivity-potential. In the second manuscript, the focus shifted to then unpacking how mobility was then produced in micro-political mobility practices (or from “below”), tracing the differential mobilities produced by people who are neurodivergent. Particularly, this manuscript interrogated the lack of research that engages with dis/abled mobilities, and the relational and lived experiences of navigating and negotiating everyday travel. Based on 30 sit-down interviews with people who identify as Autistic or with ADHD, this analysis traced the emotional influences of mobility and how focus, habit, navigation, and sensory sensitivities constructed everyday mobility practices. Further, the mobile geographies of neurodiversity were then scaffolded; examining the adaptive tactics (relating to negotiating predictability and agency/interest) that emerged and could then subvert expectations for how mobility practice ‘ought’ to function. Finally, the third manuscript examined the experiences of people who are neurodivergent in journeying everyday-transport spaces, and the ways in which differential ways-of-knowing can construct capabilities on the street. Guided by go-along interviews conducted in Waterloo, ON, this manuscript identifies specific transport-spaces that can be overwhelming or disorienting for people who are neurodivergent (including transit stations/stops, shared-spaces, and intersections). From this, recommendations were made for rescoping efforts to plan for ‘all abilities’ which consider neurodivergence and can have the potential to more-inclusively engage with the many ways in which ability is relationally and pluralistically constructed. Overall, this thesis provides transportation planning scholars and practitioners with an alternative framework for confronting the complex politics that then construct for whom streets and everyday-transport spaces function; interrogating how to more meaningfully- and mindfully- plan for ‘all abilities’ on the street and in transport spaces. Aptly, throughout this research, transportation planning, particularly complete street planning paradigms, are (re)situated within the production of mobilities as a means to close-the-gap between current complete street initiatives, and their mobility-justice potential (Sheller, 2018).
Health System Resilience for Climate Change Adaptation: An Empirical Evaluation of Access and Utilization in Western Province, Zambia
(University of Waterloo, 2025-12-18) Chiarot, Cameron B.
Background Achieving Universal Health Coverage (UHC) in low- and lower-middle-income countries (LMICs) is jeopardized by the convergence of climate-related shocks and chronic health systems stressors. In Western Province (WP), Zambia, a vast, rural, and remote area characterized by the Barotse Floodplain, progress toward UHC is hindered by the interplay between seasonal flooding variations and pre-existing challenges such as low health facility density and geographic barriers to accessing and utilizing essential primary health care services. A significant gap exists in the empirical evidence necessary to quantify these adverse synergistic interactions, improve routine surveillance systems that currently lack reliable population denominators, and develop dynamic models to assess the impact of shocks and stressors on health service utilization. Objectives This dissertation develops and applies a comprehensive methodological framework to empirically evaluate access to and utilization of essential health services in WP, Zambia. It endeavors to (1) define and measure the dimensions of access, encompassing supply- and demand-side conditions within the context of spatial and temporal parameters; (2) establish an innovative methodology for generating population denominators to enhance disease surveillance and epidemiological metrics; (3) quantify the synergistic impacts of environmental and systemic challenges on service utilization through a novel econosyndemic framework; and (4) model health system resilience dynamically by forecasting utilization patterns and evaluating the effects of various shocks and stressors over time. Furthermore, this dissertation concludes with a policy brief, representing a preliminary policy assessment (Phase I) that employs a location-allocation model to optimize the current health facility network for geographical efficiency, thereby identifying existing access gaps and redundancies within the system. This initial optimization serves as a foundation for a proposed multi-stage framework designed to generate actionable investment strategies by integrating health system capacity, cost considerations, and evolving population needs into future analyses (Phase II). Ultimately, this work offers an integrated, evidence-based framework aimed at strengthening health system resilience as a vital climate change adaptation strategy, thereby advancing the overarching objective of ensuring equitable access to healthcare for vulnerable populations. Methods This dissertation, grounded in comprehensive research, comprises four empirical studies in addition to a policy analysis. Study no. 1 employed a cross-sectional design utilizing geospatial analysis of 220 health facilities (centres and posts) to assess access through metrics such as facility density, population growth, travel durations, and personnel distribution. Study no. 2 introduced and applied an innovative Spatially Defined Catchment Area and Population Under Rooftop (SCSO-PUR) methodology, leveraging satellite data to establish denominators for 321 health facilities, as exemplified in a malaria surveillance epidemiological case study spanning 2017 to 2024. Study no. 3 presented and quantified the econosyndemic framework within an ecological longitudinal study of 62 health centres and posts from 2017 to 2023, employing beta regression and structural equation models (SEM) to analyze the interaction between flood exposure and health system capacity concerning maternal and child health, as well as overall general utilization (i.e., outpatient visits). Study no. 4 utilized time-series forecasting and an Interrupted Time Series (ITS) analysis on the same dataset to measure the dynamic effects of three distinct shocks—the 2019 drought, the 2021 COVID-19 pandemic, and the 2023 complex flood event —on overall utilization, namely outpatient visits. The Policy Brief, Preliminary Assessment (Phase I), employed a Set Covering Problem (SCP) model on the network of 321 facilities to optimize geographic coverage and identify system-wide efficiencies. Findings Geographic access constitutes a primary barrier, with projected declines in facilities per capita and estimated mean travel times ranging from 6.6 to 13.9 hours. A substantial proportion of the population (26.4%, exceeding 322,000 individuals) resides beyond the World Health Organization's recommended two-hour travel time to a comprehensive Health Centre. The SCSO-PUR methodology has demonstrated feasibility in establishing standardized denominators, thereby elucidating previously obscured spatial-demographic disparities in malaria risk. The econosyndemic framework has been empirically validated; notably, the interaction between high flood depths and health system stressors was found to significantly disrupt essential services, including antenatal care (ANC) and facility-based births. The Interrupted Time Series (ITS) analysis indicates that various shocks yield distinct and quantifiable impacts on overall utilization patterns, ranging from immediate declines (drought) to paradoxical increases (COVID-19) and gradual recoveries (i.e., complex flood event). Lastly, the health system optimization analysis uncovers significant spatial redundancy; specifically, while comprehensive geographic coverage could be theoretically achieved with only 46 of the 321 existing facilities, this would entail accepting travel times of up to 7.5 hours, thereby underscoring a crucial trade-off between efficiency and equitable access. Conclusion This dissertation provides a comprehensive, empirically grounded framework for understanding and strengthening health system resilience in a climate-vulnerable setting. It demonstrates that the adverse synergistic interaction between environmental shocks and systemic supply- and demand-side stressors creates an econosyndemic that dynamically and inequitably disrupts access to and utilization of essential health services. The novel methodologies developed offer scalable, data-driven tools for ministries of health to transition from reactive to proactive, evidence-based planning. The findings provide a clear policy directive: building health system resilience for climate adaptation requires targeted, context-specific interventions that address underlying vulnerabilities in infrastructure and geographic accessibility.
The Role of ICT MNCs in Climate Adaptation Through Disaster Response: Motivations, Technology, and Climate Security Implications
(University of Waterloo, 2025-12-18) Battikh, Joe Yousr
Climate change is intensifying the frequency and severity of natural disasters with devastating effects, particularly in developing countries where vulnerabilities are amplified, while traditional disaster management and governance systems are increasingly overstretched. These climate-driven crises, which cost billions and displace millions annually, demand urgent adaptation to mitigate their catastrophic impacts on fragile societies. Multinational corporations (MNCs), especially those from the Information and Communications Technology (ICT) sector, are emerging as critical actors in disaster response, leveraging their resources and expertise to support relief and recovery efforts. This dissertation examines the role of ICT MNCs in addressing natural disasters, and explores their interventions, motivations, and potential to mitigate climate security risks by enhancing resilience in vulnerable regions. Through a multi-method approach, including bibliometric analysis, content analysis of sustainability reports, and a qualitative case study, this research reveals the growing involvement of ICT MNCs in disaster response by utilizing their technological capabilities to bridge critical gaps. However, a concerning geographical disparity is identified with declining corporate engagement in developing countries, despite their increased vulnerability. The case study of ICT MNCs' response to the 2024 Cyclone Hidaya floods in Kenya proposes the empirically grounded TEC Response framework (Triggering response–Engagement motivation–Championing technology), illustrating how corporate interventions are triggered by local presence, driven by a complex interplay of corporate social responsibility (CSR), ethical imperatives, and strategic interests, and implemented by leveraging core technological competencies. This dissertation affirms established CSR theory and contributes novel empirical insights to private governance scholarship by providing empirical evidence of the strategic and ethical dimensions of MNC involvement in disaster contexts and by highlighting their voluntary, uneven, and often unaccountable role in disaster governance, including their capacity to mitigate or inadvertently reinforce climate-induced vulnerabilities. The findings offer practical insights for policymakers and MNCs, emphasizing the importance of cross-sector collaboration, technological integration, and long-term resilience-building to enhance equitable and sustainable disaster management and climate adaptation efforts while addressing critical gaps in mitigating climate-induced vulnerabilities in fragile settings.
Examining the influence of attentional distraction and emotional distress on gait behaviour in Functional Gait Disorders
(University of Waterloo, 2025-12-17) Girlea, Alexandra Laura
Functional Gait Disorders (FGD) are a subgroup of Functional Neurological Disorders (FND) that are characterized by the presence of abnormal postures and movements whose appearance and severity fluctuate, or are inconsistent, over time. These movements appear voluntary but are reported to be involuntary by the patient. FGD symptoms may arise from abnormalities in attentional and emotional regulation, and these dysfunctions lead to loss of agency (control) over movement. These movements may mimic those of other neurological disorders, however sensory and motor testing reveals normal function. This preservation of function despite symptom presentation is referred to as symptom incongruency. Due to the inconsistency and incongruency FGD symptoms, as well as the heterogeneity in phenomenology across individuals with FGD, diagnosis proves a challenge. Individuals with FGD often face delays and excessive costs when pursuing an appropriate diagnosis, ultimately prolonging their disability and delaying access to adequate treatment. A majority of previous work has utilized qualitative approaches to phenotype FGD and aid in diagnosis. While these approaches provided key foundational information about FGD, they do not capture all aspects of FGD. Therefore, quantitative methods of FGD may provide more insight into its phenomenology. However, there is a lack of work utilizing quantitative approaches in FGD. Existing work has primarily focused on the influence of attentional distraction on symptom presentation and severity during gait, providing mixed evidence addressing the influence of attention on functional gait. Similar to qualitative descriptions, some quantitative evidence shows an improvement in symptom presentation and severity while completing a secondary task. To date, there have been no studies investigating the effect of emotional distress on gait in FGD, and this area would be important to investigate given that emotional dysregulation is a key component of FGD phenomenology. While anxiety during gait has been manipulated with postural threat paradigms, the threat of shock paradigm has also been shown to elicit anxiety in laboratory settings. However, the threat of shock has not yet been utilized in gait research. Investigating its validity for use in gait may provide more insight into how this paradigm provokes anxiety during walking, and how walking may change during this scenario. As such, the present thesis aims to address several gaps in the literature. The first is that there are few quantitative descriptors of FGD phenomenology, therefore identifying descriptors may complement and augment qualitative observation and subsequent diagnosis. The second is that while the influence of attention has been investigated in FGD, there has been limited work done investigating the influence of emotional distress on gait in this population, despite its self-reported influence on symptom provocation. Understanding or characterizing the influence of emotional distress on gait in this group may provide novel insights for clinical diagnosis. The use of the novel threat of shock paradigm may also provide more insight into the influence of anxiety on walking in FGD. Together, the present study aimed to address these gaps by utilizing the novel threat of shock paradigm to investigate the influence of attentional distraction and emotional distress on gait behavior and symptom severity in individuals with FGD. It was expected that the threat of shock paradigm would elicit anxiety in all participants. Additionally, it was expected that the dual task would lead to normalized gait in the FGD group, and that the threat of shock would yield a worsening of gait in the FGD group. Finally, it was anticipated that greater levels of movement reinvestment in FGD patients would be associated with a greater dual-task effect on gait in this group, meaning that greater reinvesters would show a greater degree of movement normalization when completing a dual task compared to walking in the absence of a dual task. Eleven FGD patients and 17 age- and sex-matched controls completed 11 walking trials that spanned 4 conditions (neutral, dual task, shock, dual task + shock). All participants self-reported their level of anxiety after each trial, and at the end of the study, completed a battery of questionnaires addressing their movement reinvestment and anxious tendencies. The present study confirmed the utility of the threat of shock during gait, as participants reported greater anxiety when the shock was present. Interestingly, the dual task did not lead to gait normalization in FGD patients. Rather, both patients and matched controls showed worsened gait in the presence of the dual task. Additionally, the threat of shock only impacted step length variability in FGD patients, wherein patients showed greater variability compared to controls in both the presence and absence of shock. Finally, the present study revealed insights into the relationship between reinvestment and symptomology in FGD, wherein patients with a greater degree of reinvestment showed improved gait while dual tasking compared to their baseline gait. Taken together, the present study not only illustrates the utility of the threat of shock paradigm in gait assessments, but also shows nuances in the relationship between attentional distraction and FGD symptomology. Findings from the present study set the stage for future use of the threat of shock during gait, as well point to the importance of movement reinvestment in the presentation and potential resolution of symptoms in FGD. Future work should continue to investigate reinvestment in the context of FGD and should take a more nuanced and individualistic approach to better encapsulate the heterogeneity inherent in functional gait disorders. Doing so may provide a more complete picture of these disorders and may improve characterization, diagnosis, and treatment of these patients.
A Neural-network-based Solver for the Three Dimensional Shape of Vesicle Membranes
(University of Waterloo, 2025-12-17) Rohanizadegan, Yousef
A neural-network-based numerical solver is developed for computing three-dimensional (3D) equilibrium shapes of deformable biomembranes, specifically phospholipid vesicles modeled by Helfrich's curvature elasticity theory. The solver represents vesicle morphology using a phase-field formulation, in which a scalar field distinguishes the interior and exterior of the vesicle through a diffuse interface. The phase field is parameterized by a compact feedforward neural network, and the equilibrium shape is obtained by direct minimization of the Helfrich bending energy subject to global surface-area and volume constraints, enforced via Lagrange multipliers. Automatic differentiation is used to evaluate all spatial derivatives, thereby avoiding finite-difference truncation errors and explicit surface discretization. This framework produces both axisymmetric and fully non-axisymmetric vesicle shapes without imposing symmetry assumptions. Canonical free-space branches, namely prolates, oblates, and stomatocytes, are reproduced, and the classical bending-energy–reduced-volume diagram is recovered in close quantitative agreement with established results in the literature. In addition, a phase-field expression for the bilayer area-difference constraint is derived and incorporated into the solver, providing a numerical setting for the computation of non-axisymmetric equilibrium morphologies in free space. A major contribution of this work is a systematic investigation of vesicle morphology under confinement. Vesicles are studied within a range of hard-wall geometries, including cylindrical (tube), slit, spherical, and cubic confinements. By varying confinement size and reduced volume, the solver captures a rich spectrum of deformations, including biaxial squeezed states, bent prolates, squeezed stomatocytes, and cubic and clam-like morphologies. Stability diagrams, bending-energy curves, and phase diagrams are constructed for each confinement, revealing both discontinuous (first-order) and continuous (second-order) shape transitions, as well as hysteresis and metastable branches. These results extend existing confinement studies by providing fully three-dimensional, non-axisymmetric solutions across multiple geometries and different regimes of confinement (free space to weak to strong) within a unified computational framework. Overall, this work establishes a versatile and scalable neural-network-based phase-field approach for vesicle shape modeling. By unifying classical membrane elasticity theory with modern machine-learning optimization, the solver facilitates a structured exploration of equilibrium morphologies, phase transitions, and confinement effects beyond the reach of traditional axisymmetric or surface-discretization methods. The framework provides a foundation for future extensions to more complex membrane models, dynamic processes, and biologically relevant geometries in soft-matter and biophysical systems.
Investigation of Organic ETLs in QLEDs and a Metal-based RGB Patterning Technique for QLED Displays
(University of Waterloo, 2025-12-17) Mobarak, Saad
Colloidal quantum dot light-emitting devices (QLEDs) have attracted significant interest for next-generation emissive display and lighting applications owing to their narrowband emission, tunable bandgaps, and compatibility with solution-based fabrication. Their emissive layers (EMLs), composed of colloidal quantum dots (QDs), exhibit discrete energy states and size-dependent bandgaps, allowing precise spectral tunability and narrow emission linewidths (FWHM < 25 nm). The high photoluminescence quantum yield (PLQY), excellent photochemical stability, and compatibility with low-temperature fabrication processes make them highly suitable for large-area and flexible devices. Collectively, these properties position QLEDs as strong contenders to replace organic-LEDs (OLEDs) in future display technologies, offering improved color saturation, reduced power consumption, and enhanced manufacturing versatility. Despite these advantages, QLEDs still face fundamental challenges related to charge transport and device efficiency. In particular, the use of organic electron transport layers (ETLs) has been limited due to their perceived low electron mobility and inferior performance compared to inorganic metal-oxide ETLs. However, organic ETLs remain attractive for certain device architectures because of their solution processability, tunable energy levels, and compatibility with low-temperature and flexible fabrication. Moreover, organic layers can form smoother, defect-free interfaces with the QD EMLs compared to metal-oxide ETLs, which may introduce interfacial traps or cause damage during deposition. While the low efficiency of QLEDs employing organic ETLs has conventionally been attributed to their poor electron mobility, the findings presented in this thesis reveal that uncontrolled electron leakage from the QD EML to the hole transport layer (HTL) plays a more dominant role. Based on the finding, the design and optimization of multilayer organic ETL architectures with electron-blocking interfaces effectively suppress electron leakage, leading to improved charge balance and enhanced device efficiency. Using this approach, both red and green QLEDs achieve maximum EQEs approaching 10%, representing among the highest reported values for devices employing organic ETLs. Another limitation in QLEDs is their limited amenability to high-resolution patterning of RGB arrays for full-color displays. Conventional techniques, such as inkjet printing or photolithography, often suffer from limited resolution, QD degradation, or complex processing steps that can compromise device performance. This thesis also presents a novel RGB patterning technique based on metal-induced quenching. Thin metal layers are selectively deposited via a shadow mask onto target areas of the QD EMLs, where subsequent metal diffusion into the EML locally suppresses luminescence through non-radiative energy transfer, while unexposed regions retain their intrinsic emission characteristics. Optical and morphological characterization shows that metal-coated QD regions develop increased surface roughness and island-like features, indicating that metal diffusion into the QD layer plays a significant role in facilitating non-radiative quenching. Using this approach, we demonstrate the fabrication of devices containing multiple QLEDs from a single multilayer stack, each producing spectrally pure electroluminescence (EL) without detectable parasitic emission. Additional patterned structure demonstrates controlled microscale emission at the device level, establishing the feasibility of achieving spatial color definition with high precision. These results validate metal-induced quenching as an effective methodology for QLED color patterning and provide insight into metal-QD interactions.
Microfluidics meet predictive modeling: spatiotemporal characterization of antagonism in bacterial communities
(University of Waterloo, 2025-12-17) Ahmadi, Atiyeh
Microbial habitats (e.g. in the mammalian gut, in soils) are strongly spatially heterogeneous: diffusion limits, advection, and porous structure generate micron-scale gradients in nutrients, oxygen, pH, and antimicrobials. As a result, immediate neighbors can experience different exposures over time, so population-level behavior emerges from local interactions rather than averages. To explain community assembly, stability, and responses to perturbations, we therefore need to characterize interactions among bacterial populations at single-cell, spatially resolved scales. Within this landscape, antagonistic interactions (diffusible bacteriocins, contact-dependent inhibition, and competition for space/resources) are major determinants of fitness and composition, but their efficacy depends on cell-tocell variability in production, receptor status, and exposure paths. This thesis bridges single cell based experiments and predictive modeling to make those dynamics measurable and modelable at scale. I first establish a methodological foundation by benchmarking time-lapse image-processing software for bacterial populations, creating ground-truth datasets and mapping performance trade-offs to guide tool selection (Chapter 2). I then introduce TrackRefiner, a post-processing software that identifies and corrects tracking errors in time-lapse images of rod-shaped bacteria, thereby improving lineage fidelity for downstream analyses (Chapter 3). To bridge experiments and models, I survey and systematize machine-learned summary statistics for Bayesian parameter inference in systems biology (Chapter 4). Building on these elements, I present a pipeline that carries data from microfluidic image acquisition to agent-based model calibration (Chapter 5). Chapter 6 was intended to apply this toolkit to single-cell antagonism in bacterial communities, characterizing spatiotemporal interactions and developing a predictive model. Because of time constraints, I focused on building time-lapse microscopy datasets and analyzing them with the methods from Chapters 2 and 3. These analyses also help to understand aspects of the biology of the antagonistic system we study. I implemented a preliminary agent-based model to capture cell growth and toxin diffusion/uptake; calibration and validation are left for future work. Collectively, the thesis delivers (i) validated image processing practices with openly released ground truths for segmentation and tracking, (ii) open-source software that enhances tracking quality, and (iii) a reproducible calibration workflow for agent based models. To the best of my knowledge, (iv) it also presents the preliminary single-cell, spatiotemporal characterization of colicin Ib–mediated antagonism in microfluidic environments. The impact is twofold: experimentalists gain a principled framework to quantify and compare antagonistic strategies at single-cell resolution, and modelers obtain reliable, information-rich statistics for forecasting community dynamics and evaluating interventions. By unifying microfluidics with inference, the work is a step towards data-driven control and design of microbial consortia.
Machine Learning Approaches for Thermoelectric Performance Predictions
(University of Waterloo, 2025-12-17) Barua, Nikhil
The area of thermoelectric (TE) research suffers from an affordable pathway to achieve high performance TE materials. This is because the merit of the experimental approach, although sacrosanct and irrefutable, often, resorts to a trial- and-error method approach. This approach is achieved through training, experience, and observed knowledge. Additionally, while working to find an effective solution through this approach, the target TE material is kept in mind. This introduces biasness in TE materials discovery. In TE research, recent studies have demonstrated the potential for accelerated materials discovery through artificial intelligence (AI) driven methods. Building on these advances, the thesis aims to assist experimental researchers in predicting the properties for high-performance thermoelectric (TE) materials. The objective in the thesis is realized with the developed and tested machine learning (ML) models to predict TE properties. The developed models are based on extreme gradient boosting (XGBoost) and light gradient boosting machine (LightGBM) algorithms. These algorithms, which form part of the ML framework, were trained using curated datasets. The models achieved good predictive accuracy of TE properties. The interpretability of the model predictions through SHapley Additive exPlanations (SHAP), provided interesting and chemically meaningful insights between TE material compositions and the TE properties. In one of our studies, the predictive models were validated experimentally for new doped SnSe systems to observe near consistency between predicted and measured κ values. Subsequently, we developed an end-to-end web application embedded with these ML models, hosted on Git-Hub and Microsoft Azure cloud to deliver rapid TE property predictions. The application is made accessible to TE researchers worldwide. The researchers can upload any set of compositions to the web interface and receive immediate thermoelectric (TE) property predictions. The methodology of the overall ML pipeline explained in the chapters are open for diversification with other Deep Learning (DL) algorithms or Generative AI (Gen AI) models. Furthermore, the ML models can be retrained by modifying the data in the existing dataset, in the direction of improving model accuracy. With this, the models can be used for experimental or first-principle based computational validation. The scope of this research offers more questions than answers leading to an extensive scope of hypothesis generation. Therefore, this opens unlimited opportunities for future investigations.
On Asymmetric Induced Saturation
(University of Waterloo, 2025-12-17) Hajebi, Sahab
Given a graph H, a graph G is H-free if no induced subgraph of G is isomorphic to H. A graph G is H-induced-saturated if G is H-free but deleting or adding any edge in G creates an induced copy of H. The notion of induced saturation originated in a 2012 work by Martin and Smith [23] concerning the extremal properties of H-induced-saturated graphs. On the structural side, a large body of work since then has been devoted to the study of graphs H for which H-induced-saturated graphs do exist in the first place. We say that H is normal if there exists an H-induced-saturated graph. It is immediate that complete graphs (except when on two vertices) are not normal because deleting edges from a graph cannot increase its clique number. Similarly, empty graphs (except when on two vertices) are not normal because adding edges to a graph cannot increase its independence number. Beyond these trivial cases, however, characterizing normal graphs is quite difficult: The four-vertex path is the only other graph currently known not to be normal, and very few graphs are known to be normal. In particular, it remains open whether all even cycles are normal. In this thesis, we study the analogous notions with only one of the two operations – edge deletion or addition – required to create an induced copy of H. Given a graph H, we say that a graph G is H-deletion-saturated if G is H-free, has at least one edge, and deleting any edge in G creates an induced copy of H. We say that H is deletion-normal if such a graph G exists. (The complementary notions of H-addition-saturated and addition-normal are defined similarly.) These “asymmetric” weakenings of induced saturation appear to be more tractable. For example, in contrast to the fact that, as mentioned above, it remains open whether all even cycles are normal, Tennenhouse [28] proved that all even cycles are addition-normal, and with Fan, Sepehr Hajebi, and Spirkl, we proved recently [16] that all even cycles are deletion-normal. We conjecture that every non-complete graph H is deletion-normal (or equivalently, that every non-empty graph H is addition-normal), and provide evidence for our conjecture by proving it for a variety of graphs H, including all complete multipartite graphs with a unique largest part, line graphs of all trees, all triangle-free graphs with exactly one cycle, and all graphs on at most six vertices.

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