Dr. Aprahamian’s research interests lie at the interface of Operations Research and Machine Learning. Specifically, his research focuses on combinatorial/discrete optimization, and network analysis, in which he works on finding new solution techniques and efficient algorithmic approaches to solve difficult optimization problems. Applications of his work include high-dimensional cluster analysis, risk classification procedures, and large-scale screening of heterogeneous populations. He is particularly interested in applications related to healthcare systems and public policy decision-making.
