I am a machine learning and data science researcher with over 10 years of industry experience developing in-house optimization and machine learning software for prediction in high-pressure and fast-moving financial markets. I received my PhD from University of Toronto’s Department of Mechanical and Industrial Engineering under the supervision of Professor Roy Kwon. Our research is at the intersection of machine learning and decision-based optimization. Specifically we study the impact that machine learning predictions have on downstream decision-making with direct applications to portfolio optimization.

I am always interested in connecting with researchers and practitioners doing both basic-science and applied research across a variety disciplines including: data science, optimization, machine learning, finance, health care and more. If you are interested in connecting or collaborating then please reach out!

Research Interests

• Convex optimization
• Machine learning
• Differentiable optimization layers
• Integrated prediction and optimization
• Inverse optimization