Biography

Dr. Carolyn Augusta is a passionate statistics teacher and researcher.

Her current major focus in course instruction is the development of quantitative critical thinking skills for business excellence. After her formal training at the University of Waterloo and the University of Guelph, Carolyn joined the Edwards School of Business at the University of Saskatchewan in 2019. Her area of research focuses on agribusiness processes, examining and developing epidemiological applications of deep learning, machine learning, and statistical learning methodology.

Carolyn is an elected member of University Council and serves on the Academic Programs Committee and Academic Integrity Task Force.

Courses Taught

• COMM 104
• COMM 207

Research

Carolyn develops and uses statistical, machine learning, and deep learning methods in epidemiological applications with consequences for agribusiness and human health. In one of her papers, she described how diseases may spread over the swine network in Manitoba (an industry worth over $1 billion). In another, she used deep learning to classify epidemic curves to predict the course of a disease in a simulated plant population. In her final doctoral work, she used machine learning methods to predict the spread of COVID-19 in Saskatchewan.

Additionally, Carolyn developed two sets of open access course notes, each over 200 pages long with extensive examples and applications, for the free use of her students. She has recently branched out into the Scholarship of Teaching and Learning, having co-authored a book chapter on academic integrity during the pandemic.

Publications

Augusta, C. and Henderson, R.D.E., `Academic integrity in the era of COVID-19.'COVID-19 and Education: Learning and Teaching in a Pandemic-Constrained Environment, Cheong et al. (Eds.), Informing Science Institute. (2021)

Knyazev, B., Augusta, C.*, & Taylor, G. W. (2021). Learning temporal attention in dynamic graphs with bilinear interactions. Plos one,16 (3), e0247936.

Augusta, C. (2020).Infectious disease epidemiology in the era of deep learning (Doctoral dissertation, Elsevier, Wiley).

Augusta, C., Deardon, R., & Taylor, G. (2019). Deep learning for supervised classification of spatial epidemics. Spatial and spatio-temporal epidemiology,29, 187-198.

Augusta, C., Taylor, G. W., & Deardon, R. (2019). Dynamic contact networks of swine movement in Manitoba, Canada: Characterization and implications for infectious disease spread. Transboundary and emerging diseases, 66(5), 1910-1919.

• indicates co-first authorship