Research Team

The research lab is comprised of a dynamic interdisciplinary group of students and researchers, community, industry, and government partners, as well as community research leads. Membership includes students who are completing their independent study projects and/or theses in Computer Science, and/or Mathematics & Statistics, as well as paid undergraduate research assistants, graduate students, and postdoctoral fellows.

If you are interested in joining the lab, please review the list of available positions before contacting Dr. Gillis.

Former Lab Members

Keefer Rourke
Undergraduate Research Assistant

Passionate about computing, he sees technology as a force for positive change around the world, and he is thrilled to work on projects that empower communities. Keefer was involved with the eNuk project, leading the development of its web-server and client APIs. He also ran the Guelph Coding Community — a student organization for tech-focused tutorials, demos, and workshops — and, in 2019 he was awarded as the University of Guelph’s Co-op Student of the Year. In his spare time, you can find Keefer at the climbing gym where he finds dangling from heights oddly relaxing.

Brandon Edwards
Undergraduate Research Assistant

Brandon is an award-winning student who was investigating the use of mathematical modeling to better understand human impacts on the piping plover, an endangered shorebird that nests at Sauble Beach. He is currently a PhD student at Carleton University.

Graduate Students

Patrick Houlding
MSc Computer Science Student

Patrick Houlding completed a Master’s in Computer Science at the University of Guelph. Patrick has previously been involved in Dr. Gillis’ lab evaluating the Digital Divide, and has contributed to numerous other projects using statistical methods and machine learning.

Jeremie Fraeys de Veubeke
MSc Computer Science Student

Jeremie is currently pursuing an MSc in Computer Science with the goal to use natural language processing to better understand the foundational skills required to succeed in the future skills economy.

Marshall Asch
MSc Computer Science Student

Marshall Asch was a Masters student in Computer Science at the University of Guelph, where he also received his Bachelor of Computing degree. His research focus was on data storage in Mobile Mesh Networks. Marshall was named to the Society of Excellence in 2019. He currently works as a developer for Plex.

Nic Durish
MSc Computer Science Student

Nic was an MSc student in the School of Computer Science working with the Rigolet Inuit Community to quantify the digital divide. Nic won the Guelph Chamber of Commerce Young Innovators Award in 2017.

Fatemeh Safari
PhD Computational Sciences Student

Fatemeh received her B.Sc. in Computer Hardware Engineering from Shiraz University, Shiraz, Iran and completed her M.Sc. in IT Engineering – Computer Networks from Amirkabir University, Tehran, Iran, with a focus on Software Defined Networking (SDN). After several years of professional industry experience in the field of computer networks and routing protocols, she began her Ph.D. in Computational Science at the University of Guelph. She joins the Bridging the Digital Divide project with a goal of helping people around the globe with better access and connectivity given limited network infrastructure.

Hillary Dawkins
PhD Computational Sciences Student

Hillary’s PhD research has explored the use of debiasing techniques to reduce gender bias in natural language processing.

Ali Al Hadwer
PhD Computational Sciences Student

Ali recently completed his PhD investigating factors that affect the adoption of cloud-based big data analytics in the educational sector. Using a Technology-Organization-Environment framework, Ali developed a model to better understand how the factors affect adoption, and applied this to a case study for higher education in Saudi Arabia.

Jarrett Phillips
PhD Computational Sciences Candidate

Jarrett recently completed his PhD in Computational Sciences. During his program, he developed computational and statistical methods for optimal sample size determination to best capture haplotypic diversity in a species. Assessing levels of standing genetic variation within species is important for accurate and reliable specimen identification, which is only feasible with a comprehensive barcode database.

Community Research Leads

Charlie Flowers
Community Research Lead, Rigolet