Bohdan Horak is a PhD student in Statistical Machine Learning at the University of Alberta. His research focuses on machine learning and quantitative finance, with applications to credit risk, portfolio construction, and financial prediction.
He completed a bachelor’s degree with a Specialization in Mathematics and Finance and a master’s degree in Mathematical Finance at the University of Alberta before beginning his doctoral studies. Alongside his academic work, he has gained substantial industry experience in the financial sector, including roles at AIMCo, AlphaLayer, and CPP Investments.
His work lies at the intersection of statistical machine learning, financial risk modeling, and investment analytics. He has worked on applications including default prediction, churn modeling, fixed-income attribution, statistical arbitrage, and portfolio construction.
