Welcome to the Geometric Media Lab (GML).
GML was formally founded in 2018, building on our years of work in the areas of geometric methods for machine learning and vision. Over the years, our work has broadened to include extensive collaborations with applied mathematicians, statisticians, health-scientists, and media-arts that inform our work and increase its impact.
While we build a complete website, we welcome you to see our work in the links and tabs below. The primary features of work at GML include:
- Understanding the underlying phenomena of diverse media — images, video, computational sensors, wearables, to name a few.
- Mathematical methodologies from statistics, optimization, differential geometry, and topology in a manner that is motivated by physical constraints, invariance requirements, or other phenomenological considerations.
- Collaborations with researchers from diverse areas including rehabilitation, health promotion and well-being, and media-arts, which motivate the development of new algorithmic advances, as well as present challenging use-cases.
Our past and current collaborators include
Rama Chellappa, Computer Vision, University of Maryland
Anuj Srivastava, Statistics, Florida State University
Thanassis Rikakis, Media-arts, Virginia Tech
Sha Xin Wei, Media-arts, Arizona State University
Todd Ingalls, Media-arts, Arizona State University
Grisha Coleman, Media-arts, Arizona State University
Matt Buman, Health Promotion, Arizona State University
Narayanan Krishnamurthi, Interactive Neuro-Rehabilitation, Arizona State University
Aswin Sankaranarayanan, Computational Imaging, Carnegie Mellon University
Ashok Veeraraghavan, Computational Imaging, Rice University
Andreas Spanias, Signal Processing, Arizona State University
Suren Jayasuriya, Computational Imaging, Arizona State University
Robert LiKamWa, Mobile Systems, Arizona State University
Karthikeyan Natesan Ramamurthy, IBM Research AI