Suzanne M. Mahoney Senior Principal Analyst

     Over the course of her career, Ms. Mahoney has been a key player in pioneering new technologies from designing database software in the 70’s to applying Bayesian networks to DARPA-hard applications in the 90’s.  Ms. Mahoney worked for Control Data for twenty years during which time she rose from programmer-analyst to manager. In addition to technical work, she wrote proposals and managed over 20 analysts. Following a few years as a research associate at George Mason University, she worked for a small company specializing in research using Bayesian networks and developing associated leading-edge technology. She joined IDI in 2004.

In her current position, Ms. Mahoney leads efforts that model complex phenomena characterized by uncertainty, incomplete data, dynamic environments and a variety of evidence sources of varying credibility.  Applications range from object level identification and situation assessment, to the dynamic allocation of resources and aggregation of model estimates. She is particularly experienced in leveraging a combination of methods, including the elicitation of knowledge from experts, learning from available data, and automatically constructing situation specific models from a knowledge base.

EDUCATION

Ph.D, George Mason University, Information Technology, 1999.
M.A., University of Michigan, Mathematics, 1967.
B.S., University of Michigan, Mathematics, 1966.



SELECTED PUBLICATIONS AND PRESENTATIONS

Daniels, D.C., L. D. Hudson, K.B. Laskey, S. M. Mahoney,  B.S. Ware, E. J. Wright (2008) Terrorism Risk Management in O. Pourret, P. Naim, B. Marcot (eds) Bayesian Networks A Practical Guide to Applications, John Wiley and Sons, Chichester, West Sussex, England.

Mahoney, S.M. and E. Wright (2002) "Bayesian Network Engineering for Modeling Missile Defense Decisions", Proc. 2000 MSS 2002 Meeting of the MSS Specialty Group on Missile Defense Sensors, Environment sand Algorithms, Monterey, CA, February

Laskey, K.B. and S. M. Mahoney (2000) Network Engineering for Agile Belief Network Models. In IEEE Transactions on Knowledge and Data Engineering, Vol. 12, No. 7. July/August.

Mahoney, S.M. and K.B. Laskey (1998) Constructing Situation Specific Networks. In Cooper, G. and Moral, S. (eds) Uncertainty in Artificial Intelligence: Proceedings of the Fourteenth Conference, San Francisco, CA: Morgan Kaufmann.

Laskey, K.B. and S. M. Mahoney (1997) Network Fragments: Representing Knowledge for Constructing Probabilistic Models. In Gieger, D. and Shenoy, P. (eds) Uncertainty in Artificial Intelligence: Proceedings of the Thirteenth Conference, San Francisco, CA: Morgan Kaufmann.