James Sharpnack works at the intersection of machine learning and statistics, and has studied signal processing under heterogeneity assumptions such as graph structure and heteroscedasticity. Dr. Sharpnack received his Ph.D. in machine learning and statistics from Carnegie Mellon University, and is keen to apply his training to tackle important applied problems where scalability and modeling provide challenging obstacles.