Dr. Hasan Malik is faculty in quantitative analytics, specializing in volatility
modelling, peer review, and model transparency. He is known for his work in
applied machine learning for risk analysis.
Dr. Hasan Malik’s expertise spans quantitative analytics and volatility
modelling, with a focus on making machine learning models more transparent and
robust. His research explores peer review mechanisms and technical audit
practices to reduce bias and improve model reliability. Dr. Malik’s articles
have contributed to best practices in practical risk analysis and the evaluation
of model limitations.
He has worked with Canadian and international analytics teams, providing
independent model audits and developing peer review standards for emerging
analytics frameworks. Dr. Malik is an advocate for open critique and ongoing
professional development within quantitative modelling teams.
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