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Since time immemorial, not only migration to new lands have been standard patterns of human behaviour, but also the creation of narratives that commemorate founding heroes and provide aetiologies for topographical or cultural features. Most accounts still contain some historical information, others are entirely fictitious (think only of Romulus and Remus suckled by the she-wolf). Yet even the wildest fabrications articulate ethnic identity and inter-ethnic relations. The present research project is concerned with the identity constructs enshrined in such ancient foundation legends.

The widespread deployment of electric vehicle (EV) charging stations in residential areas faces several critical challenges: (i) limited availability of parking spaces, (ii) insufficient power distribution capacity to meet growing charging demands in densely populated neighbourhoods, and (iii) the high cost, long deployment timelines, and limited scalability and resiliency of state-of-the-art charging infrastructure, particularly during power system outages.

This project aims to address these challenges by developing a compact, low-footprint EV charging station based on a microgrid architecture. The proposed system will be capable of reliable operation during grid outages while minimizing adverse impacts on the utility grid under normal operating conditions. By integrating local energy resources and intelligent control, the charging station will offer enhanced resiliency, ability to expand, and cost-effectiveness compared to conventional solutions.

Natural assets are the stocks of natural resources and ecosystems that produce ecosystem services. Nature-based solutions, then, are actions we take to optimize ecosystem services use to help resolve societal challenges such as climate change adaptation and mitigation, floodwater control, environmental pollution, biodiversity loss, and threats to people's physical and mental health.

The objective of this project is to develop robust scenarios for the deployment of a marine-based carbon dioxide removal (CDR) approach that accounts for the interaction between physical (climate and ocean), technical, and social factors. Current climate projections indicate that atmospheric carbon dioxide (CO2) concentrations will exceed levels consistent with the Paris Climate Agreement target of limiting temperature increase to 1.5 to 2 ℃ making carbon dioxide removal (CDR) from the atmosphere a crucial element of national climate responses. The key question facing decision-makers is not whether to undertake CDR but which methods of CDR should be pursued. 

Financial technology, or Fintech, is a new trend that revolutionized the financial industry. Automated trading programs have become the new standard. Many of the financial activities that have been traditionally done based on human skills and experience have recently been replaced or will be replaced by computer systems. In fact, banks and investment companies are hiring more staff with strong computing skills than ever. Fintech is a broad subject and this research project is going to focus on quantitative analytics, and in particular on developing efficient and effective models for applications in finance.

Boredom has been cast as a push to action - to find something more engaging. We recently theorized that this signal arises when our cognitive and neural resources are under (or over) utilized. In other words, a basic drive (in both humans and animals) is the drive to optimally deploy our cognitive and neural resources. Our lab is now in the process of designing tasks to test this novel hypothesis, one that we think extends beyond boredom.

Statistical models play a critical role in data applications for explanatory and predictive purposes. The model-building process involves use of various statistical tools, some of which make certain assumptions to yield good statistical properties like consistency. Such properties enable researchers to make reliable statistical inferences. However, when samples are small to moderate in size, issues arise when applying common model-building tools due to deviations from underlying assumptions. Such deviations can lead to unreliable parameter estimates, reduced statistical power, thereby affecting data-driven decisions. The process of model-building and conducting statistical tests is further impeded when data are incomplete due to missing values.

This research project will utilize an existing experimental set-up at the University of Waterloo's Fire Research Facility to develop medium-scale compartment fire experiments. The candidate will form a critical part of the UW Fire Research Facility team and will benefit from collaborations and discussions with partner institutions and industry within the mass timber construction and fire safety engineering sector in Canada.

The Vision and Neurodevelopment lab is seeking applicants for full-time graduate student positions in the Vision Science Graduate Program. The successful student will join a dynamic group researching typical and atypical development of eye movements, reading, and motor ability. Specifically, the lab investigates functional consequences of pediatric eye conditions such as amblyopia (‘lazy eye’) on children on maturation of these important life skills using psychophysics, eye tracking (EyeLink 1000 Plus, Tobii Glasses 2), and body tracking (GAITRite mobile walkway, Qualisys motion capture system) techniques.