Overview

Paul is primarily interested in studying explainable machine learning (ML), digital transformation, and data science operations. He works on research that explores how stakeholders within organizations can use machine learning to make better decisions. In particular, he is studying how domain experts use model explanations to reconcile their subject-area expertise with the predictions of machine learning systems. He also studies how firms are using data science and machine learning to transform their business operations.