IET Commercial Collaborators
IET maintains an extensive and growing set of ties with leading universities in computer science, computational inference, decision analysis, mathematics, statistics, robotics, cognitive science, biology and education.
George Mason University (GMU)
GMU provides educational services for industry and government organizations in the Washington Metropolitan technology corridor, and is a leading research university in the field of information technology. The Department of Systems Engineering and Operations Research is one of GMU's strongest research departments, and offers world-recognized educational programs in systems engineering and operations research, including the nation's only civilian graduate programs in Command, Control, Communications and Intelligence and Military Operations Research. Military organizations from around the world send students to study at George Mason. GMU has worked closely with IET since 1993 to support development of IET's knowledge representation theory, model development processes and model management technology.
IET has teamed extensively with Stanford's world-class Computer Science department in areas as diverse as robotics (Professor Thomas Binford), computational inference (Professor Daphne Koller) and knowledge-based systems development (Professor Richard Fikes). With Professor Binford, IET collaborated in breakthroughs in machine vision. IET supported and collaborated with Professor Koller in her research on object-oriented Bayesian Networks. IET's ground-breaking research in evaluation of knowledge-based systems has been used to assess ontology development in multiple efforts led by Professor Fikes in Stanford's Knowledge Systems Laboratory (KSL).
Carnegie Mellon University
The Learning Systems Architecture Lab (LSAL) at Carnegie Melon University (CMU) is a research and development center at CMU that focuses on the design and creation of Internet-based technologies for education and training. IET has worked with the LSAL staff of system architects, software engineers, instructional systems designers, and research programmers to develop, utilize, and extend learning system architectures to enhance the accessibility, durability, interoperability, reusability, and cost-effectiveness of distance learning systems.