Assistant Professor at the School of Data Science and Society and Department of Statistics and Operations Research, University of North Carolina at Chapel Hill
Research lies at the intersection of machine learning, optimization, and human-model interaction
Interested in developing responsible machine learning algorithms and pipelines for high-stakes decision-making
Developed interpretable models that provably optimize accuracy and sparsity
Introduced a new machine learning paradigm called 'learning Rashomon sets' to break the interaction bottleneck by enumerating and visualizing all well-performing models