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This profile was last updated on 3/26/15  and contains information from public web pages and contributions from the ZoomInfo community.

Charles R. Twardy

Wrong Charles R. Twardy?

Research Assistant Professor

Phone: (314) ***-****  
Email: c***@***.edu
Local Address:  Washington D.C. , District of Columbia , United States
George Mason University
4400 University Drive
Fairfax , Virginia 22030
United States

Company Description: George Mason University, located in Northern Virginia and within the Washington, D.C. metropolitan area, is a doctoral granting institution with an enrollment of...   more

Employment History

Board Memberships and Affiliations


  • Ph.D.
    George Mason University
  • dual doctorate , history and philosophy of science and cognitive science
    Indiana University
41 Total References
Web References
2013 Speaker/Panelist List - Global Intel Forum, 1 July 2013 [cached]
Charles R. Twardy, Ph. D. DAGGRE forecasting project leader, George Mason University ( )
Charles R. Twardy, Ph.D., leads the DAGGRE forecasting project at George Mason University. DAGGRE combines prediction markets with Bayesian networks to improve group forecasts. It is funded by IARPA's ACE program.
Twardy received a dual doctorate in history and philosophy of science and cognitive science from Indiana University. He works on evidence and inference with a special interest in causal models. He has worked on argument mapping, information-theoretic trajectory clustering, Bayesian modeling to counter-IEDs, Bayesian credibility models for sensors and human sources, information theoretic sensor selection methods, hierarchical fusion models for image recognition, environmental models, epidemiological models and game-theoretic Bayesian networks.
Recent publications include a 2009 report to the National Research Council on Bayesian methods for intelligence analysis.
In spare moments, Twardy runs the SARBayes project, applying Bayesian search theory and machine learning to wilderness search and rescue, especially the analysis and prediction of lost-person behavior.
MDMC Members, 21 Feb 2014 [cached]
Dr Charles Twardy
Program Schedule [cached]
Chair Charles Twardy (Monash University)
Chair Charles Twardy (Monash University)
Introduction | SARBayes [cached]
SARBayes was started in late 2000 by Charles Twardy during his postdoc in the Reasoning Under Uncertainty Group at Monash University in Melbourne, Australia, with the cooperation of the Victorian Police Search & Rescue Squad, and VicWalk's Bushwalkers' Search & Rescue. (Special thanks to Rob Gatt, Vic Velthuis, and Rik Head.) From the beginning, the project has received invaluable assistance from other individuals and organizations, especially Bob Koester, Jack Frost, and Alan Washburn.
During this time Charles created the Australian database of lost person behavior and analyzing it.
With Charles and David, the AGM team developed their student project into the SORAL library, and then linked the AGM code, SORAL, and Probability Mapper, albeit loosely.
In 2005, Charles returned to the U.S. on a SBIR grant with Jim Donovan and Bob Koester, and finished the Australian Lost Person Behaviour Report (2006).
In 2008, Charles joined George Mason University as research faculty, and in 2011 began a collaboration with the WiSAR team at Brigham Young University to develop MapScore, a web portal for scoring and comparing probability maps generated by different teams and methods, using actual cases from ISRID.
"Search theory is about how to ... [cached]
"Search theory is about how to distribute your resources to most efficiently find something when you don't know where it is, but you have some idea about where it might be and how it moves," said Charles Twardy, a research professor at George Mason University and an expert on the discipline.
"You can't make the simplifying assumptions you make when they're not reacting to you," Twardy said.
"A lot of it is applying the existing search theory to land detection," said Twardy, who has contributed research on search theory to the Pentagon's Joint Improvised Explosive Device Defeat Organization.
"You need to know how good your sensors are," Twardy said. If you do, and you're aware of the environment and the target you're looking for - such as its speed and likely route - you can narrow down a measure of certainty as to what your high-priority areas should be. "Your sensors might be eyeballs, they might be sonar, they might (be) a UAV flying overhead," he added, warning that success can't be always guaranteed.
Twardy, the researcher who worked with JIEDDO, also believes that search theory may not single-handedly solve problems in big data or intelligence analysis, but he believes that the discipline will be part of the answer.
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