I am currently recruiting senior undergraduate students to join my research lab this summer. There are numerous opportunities available but I am also open to discussing other ideas you might have.
The projects (outlined below) span computer science, software engineering, data science, statistical modelling, risk assessment, community-engaged scholarship and pedagogy. In most cases, you will be working with other undergraduate and graduate students from a variety of disciplines, and with other faculty in the School of Computer Science, as well as other departments on campus.
This opportunity is open to undergraduate students at the University of Guelph who are majoring in Computer Science or Software Engineering, or have sufficient computer science or mathematics and statistics courses available to be enrolled in CIS4900 or CIS4910.
If you are interested in joining the research team, please contact me using the form at the bottom of this page. Please indicate the project number you are interested in (or describe your own), and which course code you want to use.
- Develop an R package to generalize the environmental Agent-Based Model for publication on CRAN. This will include co-authorship on a paper describing the R package and its use for evaluating risks associated with ecological or public health modelling.
- Use the environmental Agent-Based Model to model and explore scenarios related to the COVID-19 pandemic.
- Use the environmental Agent-Based Model to explore scenarios related to the management of endangered species, such as the Piping Plover.
- Optimize the Generalized Spatial Poisson Mixture Model algorithm. This will involve i) rewriting the algorithm using C, ii) parallelizing the code, and iii) building an R package for publication with CRAN. This will also include co-authorship on a paper describing the R package and how it can be used.
- Use the Generalized Spatial Poisson Mixture Model to explore cases of the flu, pneumonia, and COVID-19 in Canada.
- Help build an online interactive tool for teaching the general public about epidemics and how different mitigation strategies might impact the number of cases and deaths.
- Evaluate model selection criterion to determine which are most appropriate for use with the Generalized Spatial Poisson Mixture Model. This includes several sub-projects: i) evaluate the Deviance Information Criterion given different spatial correlation structures, ii) evaluate the Deviance Information Criterion given different number of diseases being modelled, iii) evaluate the Deviance Information Criterion given an unknown number of disease being modelled, etc.
- Help develop simulation studies to evaluate optimization algorithms to support wireless mobile mesh technology implementation.
- Assist with the development and implementation of a simulation study to evaluate the HACSim algorithm; an algorithm that provides estimates of the number of samples of a given species required to quantify haplotype variation.
- Help develop immediate feedback tools to support the delivery of the CIS3750 classroom. This includes developing Git runners to support the learning outcomes of Systems Analysis & Design in Applications.
- Help develop tools and tutorials for teaching data science methods.
- Analyze and interpret large amounts of data related to the undergraduate student educational experience using data science/statistics/machine learning methods.
- Develop an algorithm to evaluate the impact of policy changes and COVID-19 on the demographics of higher education.
- Using data that have already been collected, apply appropriate data science tools to understand the impact of foundational skills training in curricular, co-curricular, and extra-curricular settings.
- Explore case studies of software designed for Indigenous communities, with a particular focus on best practices, design tools used, and domain of application (e.g. health apps, environmental monitoring apps, games, language apps, social media).
- Explore community-engaged scholarship as a pedagogical tool for improving the educational experience of undergraduate students studying computer science & software design (specifically), and in STEM more broadly. You could identify best practices for developing a community-engaged Computer Science (or STEM) classroom, explore existing and/or develop new tools to support a community-engaged classroom, develop criteria for selecting a community partner such that their challenge meets the learning objectives of the course, and/or investigate methods in which students play a role in selecting the community-partner (and how best to deal with potential moral objections).