The University of Maryland Center for Machine Learning is a multidisciplinary center that uses powerful computing tools to address challenges in big data, computer vision, health care, financial transactions and more.
The center, part of the University of Maryland Institute for Advanced Computer Studies, incentivizes faculty, students and visiting scholars to collaborate on the latest technologies and theoretical applications based in machine learning.
Research underway includes groundbreaking work in cancer genomics; powerful algorithms to improve the selection process for organ transplants; and an innovative system that can quickly find, translate, and summarize information from almost any language in the world.
Funding for the center comes from UMD’s College of Computer, Mathematical, and Natural Sciences (CMNS) and UMIACS, with additional support provided by financial and technology leader Capital One.
His research focuses on large-scale optimization and distributed algorithms for big data. Goldstein’s work has applications in machine learning and image processing, especially for MRI and CT.
Her research focuses on machine learning, high-dimensional statistics and distributed algorithms—both the theoretical analysis and practical implementation of parallel spectral methods for latent variable graphical models.
His current research explores fast internet over hetrogenous networks, integrated management of hybrid communication networks, modeling and performace evaluation of large broadband hybrid networks, scaleable multicast security and more.