Department of Statistics & Actuarial Science
(Computational Statistics and Machine Learning)
Joined SFU in July 2015
Dr. Bornn possesses exceptional skills in statistical modeling and computation. He creates original, scalable statistical models and innovative computational approaches to identify complex patterns from immense, complex datasets. His research on high dimensional spatio-temporal data has diverse applications, including environmental and climate modeling, optical tracking in sports, and structural health monitoring. He uses stochastic computation (e.g., Monte Carlo methods) to tackle the associated computational problems.
The applications of your research range from the environment to sports. Which application affects you personally or motivates you the most?
At the moment, most of my time is focused on sports, primarily soccer and basketball. I’m also interested in problems related to the Earth’s climate. There are many statistical issues that are glossed over by climate scientists – a lot of uncertainty that is ignored – and I think there is a great opportunity for statisticians to add value in that domain.
What type of data occupies your thoughts the most?
The data I work with is primarily tracking data, for example, the locations of basketball players on the court over time, or seals in the ocean, or people trying to detect explosive devices, where you have movement and outcomes. What interests me is trying to figure out which individuals are making the best decisions for the desired outcomes, whether it be which basketball player makes the best passes, which seals take the best route for finding food, or which search and rescue members make the best use of their time in covering ground to reach a survivor.