Geometric Data Analytics

Where practical solutions and novel insights take shape

GDA develops and applies mathematical, statistical, and computational tools for the analysis of challenges in a wide range of domains including tracking, logistics, modeling, optimization, agriculture, machine learning/artificial intelligence, and biology.

Our team combines applied mathematics expertise, agile software design, and fundamental research practices to construct compelling demonstrations of research solutions and drive informed, confident decisions.

GDA was founded in 2012 by Dr. John Harer while he was a Professor of Mathematics at Duke University performing research on grants and contracts from DARPA, AFOSR, NSF, NIH, and DTRA. Today, the number of government agencies we work with has grown to include the Air Force Research Laboratory, Department of Energy, Environmental Protection Agency, NASA, National Geospatial-Intelligence Agency, National Oceanic and Atmospheric Administration, and National Security Agency.

Our philosophy

Our guiding principle is that clients and partners should be able to use our code both as stand-alone products and as a well-integrated component within their own computational systems. Our employees have decades of experience building computational resources from hardware up, including installing and configuring deep learning frameworks on heterogeneous and distributed resources including GPUs and CPUs. Our standard codebase is developed in a continuous integration environment.

GDA mixes agile software design practices with fundamental research practices to construct compelling demonstrations of research solutions to applied problems.

Our work

GDA performs on government research and development contracts, either as a prime or as a subcontractor to various larger companies. Agencies we have worked with or are working with include:

  • Defense Advanced Research Projects Agency
  • Air Force Research Laboratory
  • Department of Energy
  • Environmental Protection Agency
  • National Geospatial-Intelligence Agency
  • National Oceanic and Atmospheric Administration
  • National Science Foundation
  • National Security Agency
  • National Institutes of Health
  • Department of Homeland Security
  • Office of the Secretary of Defense
  • National Reconnaissance Office



Data Fusion

Our approaches provide a common language to leverage data from heterogeneous data streams to improve AI models over any single modality.


Machine Learning

With widespread impact of machine learning approaches, we enhance existing methodologies with computationally efficient shape features and explainable models.


Edge Analytics

We provide novel analytics for networks of sensors that operate on the edge, communicating with both each other and a central hub to achieve various mission-critical goals.


Shape Analytics

We specialize in extracting geometric descriptors from data to augment traditional data analysis with sophisticated concepts from contemporary mathematics.

Contact Us

Contact us to see how we can work together to solve interesting and complex data analysis problems.