This $349,427 CAREER grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research at The Leland Stanford Junior University (Stanford University) to develop machine learning (ML) techniques to improve the performance of discrete optimization algorithms. The project aims to address challenges in efficiently solving complex combinatorial optimization problems, such as those encountered in supply chain logistics and transportation planning, by leveraging ML to automate algorithm selection, configuration, and potentially discovery. In addition to the technical research goals, the award incorporates plans for community engagement, student training, and curriculum development to broaden participation in ML theory. The project will be conducted at Stanford University over the period from March 2024 to February 2029.
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