Thomas Hal­skov

I’m a PhD student in Economics at Copenhagen Business School. My research sits at the intersection of machine learning, causal inference, and mathematical optimization. I aim to turn data-driven systems into tools for equitable, accountable decisions. 

I design methods that make models explain themselves, quantify uncertainty, and meet fairness constraints. This helps organizations diagnose bias, justify outcomes, and deploy ML responsibly in policy, finance, and operations.