List of Announcements (details below):

C4I Seminar: Friday, Jan 24, 1:30pm, Engr. Bldg., room 4705

Please mark your calendars and plan to attend the C4I Seminar Series on Friday, Jan 24, from 1:30 pm to 2:30 pm in the Engineering Building, room 4705. Dr. Wei Sun discusses “Efficient User Assets Management by Trade-based Asset Blocks and Dynamic Junction Tree for Combo Prediction Markets.” For further information contact Deb Schenaker, (703) 993-3682, email: [log in to unmask], or visit our website


We have often heard that the collective wisdom of an informed and diverse group usually out-performs individual experts on forecasting and estimation tasks. The key question is how best to aggregate those diverse judgments.  In 2010, it wasn't known whether any system could reliably beat the simple average.  Mason is among the teams that reliably did so for two years in IARPA's ACE forecasting challenge. In June 2013 we closed down our geopolitical prediction market to create SciCast, a new and improved science & technology market. This talk discusses ongoing improvements to the SciCast forecasting engine.

Unlike other prediction markets, SciCast allows forecasters make conditional forecasts: the chance that China's lunar rover would deploy can be made to depend on a successful soft lunar landing. To avoid a combinatorial explosion, SciCast uses Bayesian networks as the underlying probability model.  But tracking the joint probability structure is not enough: markets also must track assets for each user, awarding users for correct forecasts and ensuring there is no possible world where they go negative.  Previously, we tracked assets using the same junction tree structure as the joint probability model. This approach provides fast computation of the minimum value and expected value. However, it wastes a lot of space: the majority of users trade sparsely relative to the total number of questions, and even more sparsely compared to the whole joint probability space.  Therefore most of the asset junction tree remains untouched. Worse, every time a question is added or resolved, we have to update the asset tree for all users, just in case.

We think a trade-based method can overcome this problem and be computationally efficient as well. It turned out that we can build asset blocks involving the questions being traded only, then collect them in an organized manner such as merging sub-block to its super set. Further, when computing user score and cash, we can construct an asset junction tree dynamically, based on the collection of asset blocks then use the asset junction tree for efficient computations. When questions are resolved, it is straightforward to update user's asset blocks accordingly. Basically, for any asset block which contains the resolved questions, we realize the resolving state and truncate the block.

In this presentation, I will explain in detail how the trade-based asset blocks are built and how to construct the corresponding asset junction tree dynamically. Computational examples will be demonstrated and compared with other alternative methods. For general questions about prediction markets or other background knowledge, please visit

Speaker Information

Dr. Wei Sun is a research assistant professor of the Sensor Fusion Lab and the C4I Center at George Mason University, where he works on stochastic modeling, probabilistic reasoning, optimization, decision support systems, data fusion and general operations research. Dr. Sun focuses his research on inference algorithm for hybrid Bayesian networks, nonlinear filtering, and information fusion. He is an expert in Bayesian inference and developer of several efficient inference algorithms. He is also a contributor/committer of the open-source Matlab BN toolbox. Applications of his research include tracking, fusion, bioinformatics, classification, diagnosis, etc.  Prior to joining GMU, Dr. Wei Sun was a Senior Analyst with United Airlines, Inc. and a professional Electrical Engineer in China. He is the recipient of the GMU’s Academic Excellence Award in 2003 and PhD Fellowship during 2003-2007.

Funding Opportunity: Commonwealth Research Commercialization Fund [Update]

[I included this last week.  It is a limited-submission program.  If you wish to submit a proposal, please forward to Keith Bushey ([log in to unmask]) no later January 22nd the following information:  the names of the PI, a title, target program and a brief abstract (2000 characters in laymen's term) with relevant references from the PIs along with your curriculum vitae.   PIs will be notified by noon on January 24.]

In this second of two FY2014 solicitations, CRCF offers six programs targeting Virginia's public and private colleges and universities, the private sector, nonprofit research institutions, and political subdivisions. Programs offered this round are: Commercialization, Eminent Researcher Recruitment, Facilities Enhancement Loan, Matching Funds, SBIR Matching Funds, and STTR Matching Funds. Details on these programs, including eligibility requirements and submission caps, are provided in program-specific guidelines.


     01/31/14:  letter of intent
     02/21/14:  application deadline

CRCF award recipients from previous solicitations:  

Questions: [log in to unmask]  

Mark Pullen & Nicholas Clark Receive Funding from Sierra Nevada Corp. and Air Force Research Lab

Mark Pullen and Nicholas Clark of the C4I Center received $88K from the Sierra Nevada Corporation and the Air Force Research Laboratory for their project “Academic PlugFest Follow-On Project”.

Kun Sun & Max Albanese Receive Funding from University of Washington and US Dept. of the Army

Kun Sun and Max Albanese of the Center for Secure Information Systems received $115K from the University of Washington and the U.S. Department of the Army for his project “Modeling and Analysis of Moving Target Defense Mechanisms in MANET”.

[This notice was included in my News announcements for 01/13/14, but did not include Max Albanese as one of the PIs.  The Office of Sponsored Programs is using a new format for announcing awards, and this has made it more difficult for me to identify all the PIs on an award, as well as the organization associated with the award.  Please let me know if an announcement omits relevant information.]


Stephen G. Nash
Senior Associate Dean
Volgenau School of Engineering
George Mason University
Nguyen Engineering Building, Room 2500
Mailstop 5C8
Fairfax, VA 22030

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Phone: (703) 993-1505
Fax: (703) 993-1633