The mission of the undergraduate program in Architectural Design is to develop students' ability to integrate engineering and architecture in ways that blend innovative architectural design with cutting-edge engineering technologies. Courses in the program combine hands-on architectural design studios with a wide variety of other courses. Students can choose from a broad mix of elective courses concerning energy conservation, sustainability, building systems, and structures, as well as design foundation and fine arts courses. In addition to preparing students for advanced studies in architecture and construction management, the program's math and science requirements prepare students well for graduate work in other fields such as civil and environmental engineering, law, and business.
Civil and Environmental Engineering
This pre-professional program balances the fundamentals common to many specialties in civil engineering and allows for concentration in structures and construction or environmental and water studies.
Energy Resources Engineering
Gain engineering skills while also exploring the many facets of the energy industry including renewable energy resources, oil and gas recovery, geothermal engineering, and more. The program allows students flexibility in exploring the evolution of energy, while providing an earth sciences based approach to energy resources.
The Engineering Physics program is designed for students who have an interest in and an aptitude for both engineering and physics. Students begin with a year of mathematics and calculus-based physics, and then proceed to depth courses in physics and engineering, as well as elective courses in a selected specialty area (Aerospace Physics, Biophysics, Computational Science, Electromechanical System Design, Energy Systems, Materials Science, Photonics, or Renewable Energy).
Mathematical and Computational Science
Study the mathematics basic to all the mathematical sciences and an introduction to concepts and techniques of computation, optimal decision making, probabilistic modeling and statistical inference.