AI Seminar Series 2022: Roberto Vega

The AI Seminar is a weekly meeting at the University of Alberta where researchers interested in artificial intelligence (AI) can share their research. Presenters include both local speakers from the University of Alberta and visitors from other institutions. Topics can be related in any way to artificial intelligence, from foundational theoretical work to innovative applications of AI techniques to new fields and problems.

On March 4, Roberto Vega — a Ph.D. student in the Statistical Machine Learning program at the University of Alberta — presented "SIMLR, Machine Learning inside an SIR model for COVID-19 forecasting" at the AI Seminar.

Accurate forecasts of the number of newly infected people during an epidemic are critical for making effective timely decisions. Vega’s presentation explores using a SIMLR model to help make more accurate forecasts — incorporating machine learning (ML) into the traditional SIR forecast model. For each region, SIMLR tracks the changes in the policies implemented at the government level, which it uses to estimate the time-varying parameters of a SIR model for forecasting the number of new infections one to four weeks in advance. It also forecasts the probability of changes in those government policies at each of these future times, which is essential for longer-range forecasts. The team applied SIMLR to data from Canada and the United States, and show that its mean average percentage error is as good as state-of-the-art forecasting models, with the added advantage of being an interpretable model. They expect that this approach will be useful not only for forecasting COVID-19 infections but also in predicting the evolution of other infectious diseases.

Watch the full presentation below:

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