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About

  • Who We Are

    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.

  • Collaboration is Key

    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 Areas

    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.

  • Our Sponsors

    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.

Our Faculty

David Jacobs

Professor of Computer Science

His research focuses on human and computer vision, especially in the areas of object recognition and perceptual organization.

John Dickerson

Assistant Professor of Computer Science

His research is at the intersection of computer science and economics with a focus on solving practical problems using stochastic optimization and machine learning.

Soheil Feizi

Assistant Professor of Computer Science

His research focuses on understanding various theoretical and practical aspects of machine learning and statistical inference problems.

Tom Goldstein

Assistant Professor of Computer Science

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.

Mohammad Hajiaghayi

Professor of Computer Science

His research focuses on designing algorithmic frameworks for complex network systems, in areas like game theory, graph theory, social networks and more.

Furong Huang

Assistant Professor of Computer Science

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.

Aravind Srinivasan

Professor of Computer Science

His research focuses on randomized algorithms, networking, social networks, combinatorial optimization, and their growing confluence in society, like in social media and public health.