Information theory, information processing and data analyses are the major thread connecting most of the scientific studies trying to understand reality with the available information. This view is at the heart of the Info-Metrics Institute.
The Info-Metrics Institute is hosted within the College of Arts and Sciences at American University. Info-Metrics is an interdisciplinary research center that fosters development of innovative and interdisciplinary research on new methods to solve problems related to real world data. The Institute provides an interdisciplinary research environment for advancing theoretical and applied work on information processing, econometrics, statistics and information theory with an emphasis on studying problems and data across the social and natural sciences.
The advancement of information processing, econometrics and statistics in general and information theoretic econometrics/statistics in particular will be accomplished via
- research and cooperation with scientists across disciplines
- joint work with applied researchers
- dissemination of knowledge through seminars, workshops and conferences
- graduate and post-graduate level five-day, full day, courses.
This Institute is unique in structure and emphasis. First, it is an active interdisciplinary research center developing new ideas and new methods for understanding unobserved structures from observed, noisy and limited data. Second, it provides training for researchers across the sciences and pursues research into new and evolving areas in information processing in general and in econometrics and statistics in particular. Third, the Institute’s researchers work with applied researchers to jointly develop the best way to understand the available data, resolve questions related to specific policies and apply these techniques to a range of important research questions. Fourth, in conjunction with the above research, the Institute engages in knowledge dissemination and graduate and post-graduate level teaching on state of the art topics in econometrics, statistics and other applied research.
