This $798,712 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research by Rutgers, The State University to develop innovative computational methods that integrate classical and quantum algorithmic tools for applications in statistics and operations research.
The key objectives are to: 1) Develop quantum-enhanced algorithms for decision-making under uncertainty in single-stage and multi-stage settings, as well as quantum-accelerated multilevel Monte Carlo methods; 2) Achieve quadratic speed-ups for solving stochastic optimization problems compared to classical approaches; and 3) Explore quantum accelerated algorithms for computing expectations under various equilibrium distributions. The project aims to enable significant advances in efficient Bayesian inference and machine learning procedures, benefiting practitioners across scientific domains. Educational and outreach efforts will broaden participation in the use and application of novel quantum computing methods.
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