Stefan Vladusic

I’m a recent master’s graduate from the University of Waterloo’s computational mathematics program. I’m broadly interested in machine learning and statistics, and more specifically in the intersection of deep learning and climate modelling. Under the co-supervision of Prof. Chris Bauch and Prof. Chris Fletcher, I completed a major research project about utilizing deep learning techniques to detect circulation tipping points in low-order models of the Atlantic ocean, and the limitations thereof. You can view the project report here. The source code for the project will soon be uploaded on my GitHub profile.

Before coming to Waterloo, I completed a master’s degree in financial mathematics from McMaster university, and a bachelor’s degree in physics and philosophy from the University of Toronto. At the former, I completed an industrial research project on the relationship between Value-at-Risk models with Gaussian market processes, and ISDA’s Standard Initial Margin Model (SIMM). At the latter, I completed a research project focused on causal models of the Einstein-Podolsky-Rosen-Bohm correlations.

Outside of academia, I have worked as a junior data scientist at Praemo Inc. There, I helped develop a model that detects sudden mode shifts in time series of Industrial Internet of Things (IIoT) data. I have also worked as an intern model audit analyst at Scotiabank’s Global Banking and Markets team, where I helped review and implement pricing and margin models for quarterly internal audits.

In my free time, I’m interested in sound design, and spend a lot of time tinkering with various plug-ins, DAWs, and some Max. I also spend my time trying to keep up with philosophy, watching and playing basketball, learning about global transit systems, and playing far too much Tetris.