I am currently recruiting undergraduate and graduate students, and postdoctoral fellows to support the Mobile Mesh Technology For Improved Connectivity In Canada research program. For more information on this research program, including the specific projects available and how to apply, please click below:
Additionally, I am looking for students interested in pursuing undergraduate independent studies, or graduate work in the following areas (presented in no particular order):
Computer Science (Mesh Technology & The Digital Divide, Decolonization & Indigenization Of Software Design, Pedagogy, Community-Engaged Scholarship, And Risk Assessment)
- CIS4900/CIS4910 students to assist with the development of community-identified and community-led web and mobile (Android or iOS) applications for data collection and information sharing in remote northern communities.
- CIS4900/CIS4910 students to develop scientific outreach media and programs for elementary and high school students in remote Indigenous communities, with a focus on STEM and Computer Science, that are grounded in current best pedagogical practices.
- CIS4900/CIS4910 students to 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).
- CIS4900/CIS4910 students to 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. Students 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,
- evaluate the effect of community-engaged learning on different elements of the student experience,
- evaluate the effect of community-engaged classrooms on the community,
- explore intellectual property rights pertaining to systems developed with and for the community in a community-engaged classroom,
- develop criteria for selecting a community partner such that their challenge meets the learning objectives of the course, or
- investigate methods in which students play a role in selecting the community-partner (and how best to deal with potential moral objections).
- CIS4900/CIS4910 students to apply a novel environmental Agent-Based Model to explore different ecological and conservation challenges, or to evaluate different management practices.
- CIS4900/CIS4910 students to help develop and optimize R packages for 1) spatial risk assessment, and 2) a novel environmental Agent-Based Model.
- CIS4900/CIS4910 students to analyze and interpret large amounts of data related to the undergraduate student educational experience.
- CIS4900/CIS4910 students to conduct a survey of teaching practices in Computer Science and other STEM disciplines, with a particular focus on warm-up activities, engagement activities, use of technology, the structure of course outlines and rubrics, and their potential relationship to student experience and outcomes.
- CIS4900/4910 students to help update and develop teaching tools and materials for the delivery of CIS3750, and CIS4020.
Mathematics & Statistics (Spatial Statistics, Bayesian Analysis, And Public Health & Ecological Risk Assessment)
- MATH4600/STAT4600 students to determine the most appropriate form of the Deviance Information Criterion (as per Spiegelhalter, 2002, and Celeux, et al., 2006) for evaluating spatial Poisson mixture models.
- MATH4600/STAT4600 students to apply a novel environmental Agent-Based Model to explore different ecological and conservation challenges, or to evaluate different management practices.
- MATH4600/STAT4600 students to help develop and optimizeR packages for 1) spatial risk assessment, and 2) a novel environmental Agent-Based Model.
- MATH4600/STAT4600 students to analyze and interpret large amounts of data related to the undergraduate student educational experience and its relationship to student learning outcomes.