Geospatial Computer Sciences Program

Program Description

The Geospatial Computer Science (GSCS) doctoral program is an interdisciplinary program  intended to train geospatially minded computer science scholars into accomplished researchers able to make significant contributions in geospatial computing. Students learn important fundamental theory in computation and geospatial science and apply it towards cutting-edge research in areas such as those listed below. The GSCS program is a unique combination of computer science and geospatial science able to position graduates as leaders in the field of geospatial computer science.

The Geospatial Computer Science Ph.D. program will:

  • Develop students into experts in geospatial computer science.
  • Train students to conduct and publish new research in geospatial computer science, including such topics as big data analytics for geocomputation, autonomous systems, remote sensing, structure from motion photogrammetry, machine learning-driven geospatial knowledge discovery, mobile computing for location-based services, and high-performance computing for spatial optimization.
  • Produce researchers who will be able to pursue careers in higher education, government, or industry related to or affected by geospatial computer science.
  • Educate students in the collecting, processing, analyzing, and visualizing of geospatial data, as well as the utilization of geospatial methods and data for developing new technologies.
  • Provide students with a rigorous preparation to use computer science theoretical and applied techniques to pursue research and scholarship that will advance the state of knowledge in geospatial computer science.
Student Learning Outcomes

Student Learning Outcomes

The program's student learning outcomes are for students to:

  • Produce innovative research that advances theory or methodology in geospatial computing science.
  • Participate at academic conferences and publish in peer-reviewed journals.
  • Find employment in research departments of public and private organizations, in major academic institutions, and in industry.
  • Advance the science of computing to create new algorithms and applications for geospatial challenges.
  • Acquire the computer science and geospatial analysis skills necessary to advance the theory and methodology of geospatial computing science.
  • Develop the professional skills necessary to present research outcomes orally to a professional or general audience as well as in writing for peer reviewed journals and conference proceedings.