The Info-Metrics Institute at American University has announced three inaugural recipients of the Info-Metrics Institute Research Prize: Jens Hainmueller, Associate Professor of Political Science at Stanford University; Justin Kinney, Assistant Professor of Quantitative Biology at Cold Spring Harbor Institute; and Nataly Kravchenko-Balasha, Assistant Professor at the School of Medicine at the Hebrew University.
"We are very excited to announce the first group of Info-Metrics Institute Research Prize recipients," said Amos Golan, director of the Info-Metrics Institute and professor at American University and an external professor at the Santa Fe Institute. "We congratulate the winners and hope that these prizes will encourage them and others to continue their important research within all areas of info-metrics."
"These awards will encourage the ongoing efforts of those applying information theory to important problems, both old and new," added Michael Stutzer, an affiliate at the Info-Metrics Institute and professor of finance at the University of Colorado in Boulder, who also chairs the Award Committee.
The prizes reward outstanding early career research. The prizes are intended for scholars across all disciplines who earned their doctorate degree within the decade prior to the nomination deadline. They recognize scholars who have creatively used info-metrics methods in their respective disciplines, with the potential for significant impact in those disciplines. The winners will receive a certificate, monetary award and admission to the Institute as a research associate, where they can benefit from the Institute's array of activities and research meetings.
Prize winners will be acknowledged at the first conferences held by the Institute following the announcement.
Kinney is being recognized for his study of equitability of mutual information as a measure of statistical dependence, and for development of information theoretic statistical techniques for analyzing genomic data.
"This recognition of my work is very much appreciated. I eagerly look forward to learning more about the Info-Metrics institute and how I might participate in its activities," said Kinney.
Kravchenko-Balasha is being recognized for the use of maximum entropy-style approaches and surprisal analysis specifically, in the identification of core patterns of activity in genetic networks and prediction of spatial distribution of cells in cultures.
"Thank you so much for this exciting news - it is a big honor," said Kravchenko-Balasha, who just accepted a position at the Hebrew University, following a Postdoc position at Caltech. "I am very happy to accept my invitation to become an Info-Metrics Research associate."
Hainmueller is being recognized for developing an entropic approach to correcting for confounding variates in the ubiquitous binary treatment studies, and providing evidence that this can perform better than commonly used propensity scoring methods.
"This is very encouraging," said Hainmueller.
The Info-Metrics Institute Research Prize was established in memory of Professor Halbert L. White, Jr., one of the Institute's founding members, who passed away on March 31, 2012.
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About the Info-Metrics Institute:
Founded in 2009, the Info-Metrics Institute is an interdisciplinary research institute dedicated to the study and dissemination of info-metrics - the science and practice of inference and quantitative information processing. It is applicable to all sciences and provides the universal mathematical and philosophical foundations for inference with finite, noisy or incomplete information. The study of info-metrics helps resolve a major challenge to all scientists and all decision makers of how to reason (optimize) under conditions of incomplete information.
The Institute is located at American University and consists of many academic affiliates from across the world, and from across a broad spectrum of disciplines from philosophy through the natural and social sciences.
For more information about the Info-Metrics Institute, visit http://www.american.edu/cas/economics/info-metrics/.