Kansas City, Mo (PRWEB) March 08, 2017
Kansas City Machine Learning Group has entered into an agreement to collaborate with Kansas State University on their “Data and Networks Optimization Design and Experimentation (DNODE)” project. Kansas City Machine Learning Group will be a collaborative partner with Kansas State on the project and will facilitate interactions between project participants (faculty and students) and companies that focus on network-type data analysis, with the goal of helping faculty identify industry collaborators and helping students find internships and job opportunities.
The Data and Networks Optimization and Experimentation project will be conducted by the research team including Dr. Pietro Poggi-Corradini, Dr. Nathan Albin, Dr. Doina Caragea, Dr. Michael Higgins and Dr. Caterina Scoglio. This highly interdisciplinary team will research the theory and applications of discrete p-modulus, a highly flexible tool that generalizes classical graph-theoretic objects such as max flow/min cut, shortest path, and effective resistance.
Founded by Brian J. Curry, Kansas City Machine Learning Group is an organization focused on creating a Machine Learning, Data Science and Artificial Intelligence hub in Kansas City.
