Neal Wagner, Ph.D.

Technical Staff

MIT Lincoln Laboratory - Cyber Analytics and Decision Systems Group

E-mail: neal.f.wagner@gmail.com, neal.wagner@ll.mit.edu

Website: http://nealwagner.org/

 

EDUCATION:

1999-2005                   Ph.D., Information Technology

University of North Carolina at Charlotte (Charlotte, NC USA)

                                    Dissertation title: “Time Series Forecasting for Non-static

                                    Environments: the DyFor Genetic Program Model”

                                    (Under the supervision of Dr. Zbigniew Michalewicz,

                                    http://www.cs.adelaide.edu.au/~zbyszek)

 

1989-1993                   M.S., Computer Science

                                    University of North Carolina at Charlotte (Charlotte, NC USA)

                                    Thesis title: “A Universally Testable Logic Element”

 

1984-1989                   B.A., Mathematics (Physics minor)

                                    University of North Carolina at Asheville (Asheville, NC USA)

 

EMPLOYMENT:

2013 – Present            Technical Staff

                                    MIT Lincoln Laboratory  –  Cyber Analytics and Decision Systems Group

                                    Lexington, MA USA

2010 – 2013                Assistant Professor of Information Systems

                                    Fayetteville State University

                                    Fayetteville, NC USA

2012 – 2012                Visiting Scientist

Summer Research Exchange Program

                                    MIT Lincoln Laboratory  –  Cyber Systems and Technology Group

                                    Lexington, MA USA

2008 – 2010                Prediction Software Designer and Project Manager

                                    SolveIT Software

                                    Adelaide, SA Australia

2005 – 2008                Assistant Professor of Computer Science

                                    Augusta University

                                    Augusta, GA USA

1999 – 2005                Instructor, Dept. of Computer Science

                                    University of North Carolina at Charlotte

                                    Charlotte, NC USA

2002 – 2005                Instructor, Dept. of Business Information Systems

                                    University of North Carolina at Charlotte

                                    Charlotte, NC USA

1995 – 1999                Computer Engineer

InterGraph Electronics

                                    Mountain View, CA USA

1993 – 1995                US Peace Corp Volunteer – Instructor of Math/Physics

                                    Lumumba College

                                    Zanzibar City, Tanzania, East Africa

 

 

RESEARCH: 

Peer-reviewed publications:

1.      Wagner, N., Sahin, C.S., Winterrose, M., Riordan, J., Pena, J., Hanson, D. and Streilein, W.W., Towards Automated Cyber Decision Support: A Case Study on Network Segmentation for Security. 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Symposium on Computational Intelligence for Cyber Security (CICS), December 2016. Available at: http://ieeexplore.ieee.org/document/7849908/.

2.      Winterrose, M.L., Carter, K.M., Wagner, N. and Streilein, W.W., Balancing Security and Performance for Agility in Dynamic Threat Environments. 2016 IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 607-617, July 2016. Available at: http://ieeexplore.ieee.org/abstract/document/7579776/.

3.      Wagner, N., Şahin, C. Ş., Winterrose, M., Riordan, J., Hanson, D., Peña, J., and Streilein, W. W. Quantifying the Mission Impact of Network-level Cyber Defensive Mitigations. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, Online available 2016, 1548512916662924. Available at: http://dms.sagepub.com/content/early/2016/08/15/1548512916662924.abstract

4.      Agrawal, V., Lightner, C., Lightner-Laws, C., and Wagner, N. A Bi-criteria Evolutionary Algorithm for a Constrained Multi-depot Vehicle Routing Problem. Soft Computing, pp. 1-20, 2016. Available at: http://link.springer.com/article/10.1007/s00500-016-2112-3

5.      Wagner N., Sahin C., Hanson D., Pena J., Vuksani E., and Tello B., Quantitative Analysis of the Mission Impact for Host-Level Cyber Defensive Mitigations, Proceedings of the 2016 ACM Spring Simulation Multi-Conference - Annual Simulation Symposium, April, 2016. Available at: http://dl.acm.org/citation.cfm?id=2962376. Received the 2016 Annual Simulation Symposium "Best Paper Runner Up" Award.

6.      Lightner-Laws C., Agrawal V., Lightner C., and Wagner N., An Evolutionary Algorithm Approach for the Constrained Multi-Depot Vehicle Routing Problem, International Journal of Intelligent Computing and Cybernetics, Vol. 9, No. 1 pp. 2-22, 2016. Available at: http://www.emeraldinsight.com/doi/abs/10.1108/IJICC-06-2015-0018

7.      Wagner N., Lippmann R., Winterrose M., Riordan J., Yu T., and Streilein W., Agent-based Simulation for Assessing Network Security Risk due to Unauthorized Hardware, in Proceedings of the 2015 ACM Spring Simulation Multi-Conference - Agent Directed Simulation Symposium, Alexandria, VA, April, 2015. Available at: http://dl.acm.org/citation.cfm?id=2872541. Received the 2015 Agent Directed Simulation Symposium "Best Paper" Award.

8.      Priest B., Vuksani E., Wagner N., Tello B., Carter K., and Streilein W., Agent-Based Simulation in Support of Moving Target Cyber Defense Technology Development and Evaluation, in Proceedings of the 2015 ACM Spring Simulation Multi-Conference - Communications and Networking Simulation Symposium, Alexandria, VA, April, 2015. Available at: http://dl.acm.org/citation.cfm?id=2872553

9.      M. L. Winterrose, K. M. Carter, N. Wagner, and W. W. Streilein,  Adaptive Attacker Strategy Development Against Moving Target Cyber Defenses, in Proceedings of MODSIM World 2014, Hampton, VA, April 15-17, 2014.

10.  Wagner, N. and Agrawal, V., An Agent-based Simulation System for Concert Venue Crowd Evacuation Modeling in the Presence of a Fire Disaster, Expert Systems with Applications, Vo1 41, Issue 6, 2014, pp. 2807-2815. Available at: http://www.sciencedirect.com/science/article/pii/S0957417413008270

11.  Wagner, N. And Agrawal, V., Using an Evolutionary Algorithm to Solve the Weighted View Materialisation Problem for Data Warehouses, International Journal of Intelligent Information and Database Systems, Vol 7, No. 2, 2013. Available at: http://www.inderscience.com/info/inarticletoc.php?jcode=ijiids&year=2013&vol=7&issue=2

12.  Schellenberg S., Mohais A., Ibrahimov M., Wagner N., and Michalewicz Z., A Fuzzy-Evolutionary Approach to the Problem of Optimisation and Decision Support in Supply Chain Networks, chapter in Variants of Evolutionary Algorithms for Real-World Applications, Chiong R., Weise T., and Michalewicz Z. (Eds.), 2012. Available at: http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-642-23423-1

13.  Mohais A., Schellenberg S., Ibrahimov M., Wagner N., and Michalewicz Z., An Evolutionary Approach to Practical Constraints in Scheduling: A Case-Study of the Wine Bottling Problem, chapter in Variants of Evolutionary Algorithms for Real-World Applications, Chiong R., Weise T., and Michalewicz Z. (Eds.), 2012. Available at: http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-642-23423-1

14.  Wagner N., DiRenzo J., and Maule B., Resource Allocation Optimization in Alien Migration Interdiction Operations Using an Evolutionary Algorithm Technique, presented at The 2012 USCG/CREATE Maritime Risk Symposium, University of Southern California, Los Angeles, CA, November 14-16, 2012.

15.  Wagner, N. and Agrawal, V., Emergency Decision Support Using an Agent-based Modeling Approach, Proceedings of the 2012 IEEE International Conference on Intelligence and Security Informatics, Washington, DC, June 11-14, 2012.

16.  Stringham, E. and Wagner, N. Property Rights Without the State: The Emergence of Property Among Agent Based Whalers, presented at The 37th Annual Conference of The Association of Private Enterprise Education (APEE-2012), Las Vegas, NV, April 1-3, 2012.

17.  Wagner, N., Michalewicz, Z., Schellenberg, S., Chiriac, C., and Mohais, A., Intelligent Techniques for Forecasting Multiple Time Series in Real-world Systems, International Journal of Intelligent Computing and Cybernetics,Vol 4: No. 3, 2011. Available at:  http://www.emeraldinsight.com/journals.htm?issn=1756-378x&volume=4&issue=3&PHPSESSID=10dv0ttcrp1isvajtjkimt8af3. The article attained 766 full-text downloads in 2011 and received the 'Most Downloaded Paper Award' from the International Journal of Intelligent Computing and Cybernetics. (View certificate here.)

18.  Ibrahimov M., Wagner N., Mohais A., Schellenberg S., and Michalewicz Z., Comparison of cooperative and classical evolutionary algorithms for global supply chain optimisation, Proceedings of the 2010 IEEE World Congress on Computational Intelligence, Barcelona, Spain, 18-23 July 2010.

19.  Mohais A., Schellenberg S., Ibrahimov M., Wagner N., and Michalewicz Z., Time-varying constraints and other practical problems in real-world scheduling applications, Proceedings of the 2010 IEEE World Congress on Computational Intelligence, Barcelona, Spain, 18-23 July 2010.

20.  Schellenberg S., Mohais A., Wagner N., Ibrahimov M., and Michalewicz Z., Optimising supply chain networks by means of a hybridised simulation-based approach, Proceedings of the 2010 IEEE World Congress on Computational Intelligence, Barcelona, Spain, 18-23 July 2010.

21.  Wagner N. and Michalewicz Z., Adaptive and Self-adaptive Techniques for Evolutionary Forecasting Applications Set in Dynamic and Uncertain Environments, chapter in Foundations of Computational Intelligence Volume 4: Bio-Inspired Data Mining, Series: Studies in Computational Intelligence, Vol. 204 Abraham, Ajith; Hassanien, Aboul-Ella; Carvalho, Andre Ponce de Leon F. de (Eds.), 2009. Available at: http://www.springer.com/engineering/book/978-3-642-01087-3

22.  Wagner, N. and Thompson, M., Forecasting the Periodic Net Discount Rate with Genetic Programming, Journal of Business Valuation and Economic Loss Analysis: Vol. 4 : Iss. 1, Article 4, 2009. Available at: http://www.bepress.com/jbvela/vol4/iss1/art4

23.  Michalewicz Z., Ibrahimov M., Schellenberg S., Mohais A. and Wagner N., Application of Evolutionary Methods for Complex Industrial Problems, Proceedings of EUROGEN 2009, T. Burczynski and J. Periaux (Eds),  2009.

24.  Wagner N., Khouja M., Michalewicz Z., and McGregor R., Forecasting Economic Time Series with the DyFor Genetic Program Model, Applied Financial Economics,Vol. 18 Issue 5, 2008. Available at: http://cats.tfinforma.com/PTS/in?t=rl&o=au&m=194832

25.  Wagner N. and Michalewicz Z., An Analysis of Adaptive Windowing for Times Series Forecasting in Dynamic Environments: Further Tests of The DyFor GP Model, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2008), Atlanta, GA, USA, July 12-16, 2008.

26.  Wagner N. and Michalewicz Z., Parameter Adaptation for GP Forecasting Applications, chapter in Parameter Setting in Evolutionary Algorithms, Lima C., Lobo F., and Michalewicz Z. (Eds.), Springer Series Studies in Computational Intelligence,  2007.  Available at: http://www.springer.com/engineering/book/978-3-540-69431-1

27.  Wagner N., Michalewicz Z., Khouja M., and McGregor R., Time Series Forecasting for Dynamic Environments: the DyFor Genetic Program Model, IEEE Transactions on Evolutionary Computation, Vol. 11 No. 4, 2007.  Available at: http://ieeexplore.ieee.org/xpl/tocresult.jsp?isYear=2007&isnumber=4280853&Submit32=View+Contents

28.  Carreno E., Leguizamon G., and Wagner N., Evolution of Classification Rules for Comprehensible Knowledge Discovery, Proceedings of the 2007 IEEE Congress on Evolutionary Computation (CEC-2007), Singapore, September 25-28, 2007.

29.  Wagner N. and Brauer J., Using Dynamic Forecasting Genetic Programming (DFGP) to Forecast U.S. GDP with Military Expenditure as an Explanatory Variable, Defence and Peace Economics, Vol. 18(5), 2007. Available at: http://www.informaworld.com/smpp/1686289569-26818918/title~db=all~content=g781328817

30.  Wagner N. and Brauer J., Forecasting U.S. GDP and Military Expenditure using Dynamic Forecasting Genetic Programming (DFGP), Proceedings of the 2006 Turkish Economic Association International Conference on Economics, Ankara, Turkey, September 11-13, 2006.

31.  Wagner N., Michalewicz Z., Khouja M., and McGregor R., Time Series Forecasting for Dynamic Environments: the DyFor Genetic Program Model, Proceedings of the 2005 International Seminar on Soft Computing and Intelligent Systems (WISIS'04), 2005.

32.  Wagner N., Michalewicz Z., Khouja M., and McGregor R., The DyFor Genetic Program Model: Time Series Forecasting with a Dynamic Data Window, Proceedings of the 2005 International Symposium on Intelligent Computation and Its Applications, Wuhan, China, April 4-6, 2005.

33.  Wagner N., Michalewicz Z., Khouja M., and McGregor R., Forecasting with a Dynamic Window of Time: the DyFor Genetic Program Model, Proceedings of the 2005 International Workshop on Intelligent Media Technology for Communicative Intelligence, Warsaw, Poland, September 13–14, 2004, Springer-Verlag, Lecture Notes in Computer Science, 2005.

34.  Johnson R., Melich M., Michalewicz Z., Schmidt M., and Wagner N., Coevolutionary Approach for Strategic Decision Support, Proceedings of 7th Asia-Pacific Conference on Complex Systems (Complex-2004), Cairns, Australia, December 6-10, 2004.

35.    Wagner N. and Michalewicz Z., Genetic Programming with Efficient Population Control for Financial Time Series Prediction, Proceedings of the 2001 Genetic and Evolutionary Computation Conference (GECCO-2001) Late Breaking Papers, San Francisco, CA USA, July 7-11, 2001.

 

Research Interests:

My research area is in the field of computational intelligence, specifically evolutionary and bio-inspired algorithms and their application to real-world problems in the areas of homeland and cyber security, emergency management, supply chain management, econometric modelling, and engineering design. Evolutionary Algorithms (EA) uses Darwin’s theory of “survival of the fittest” as a model for designing computer programs that automatically “evolve” solutions to a particular problem. Bio-inspired algorithms use biological processes as models for designing computer programs that solve problems. Ant colony optimization, agent-based modelling, artificial immune systems, neural networks, swarm intelligence, and others along with EA are examples of bio-inspired algorithms.

 

These techniques are nature’s way of finding an optimal or near-optimal solution when the number of possible solutions is too large for a conventional (deterministic) algorithm to handle. Many real-world problems require searching a solution space that is quite large (e.g. resource allocation, design optimization, large group emergent behaviour, prediction of dynamic systems) and, thus, bio-inspired computing techniques appear promising.

 

Commercialization of Research Interests and Industry Experience:

I have been involved in a number of projects that are industry applications of evolutionary prediction and optimization.

 

2009 – 2010 Food product demand prediction and stock replenishment optimization:

A major Australian food distribution company contracted services for the delivery of an integrated system to predict product demand and automatically replenish stock for over 15,000 products at 60+ distribution sites throughout Australia.  Designed the system, lead the implementation team, and managed the project. The system has been in live use since October 2009 with hundreds of stock items being replenished via the system daily.

Example screenshots:

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2010 Entertainment asset demand prediction and yield optimization:

An Australian-based kiddie ride company contracted services for the delivery of an integrated system to predict demand of kiddie rides at shopping centers across Australia and automatically create ride transfer plans that switch locations of rides to keep the interest fresh and maximize profit.  Designed the system, lead the implementation team, and managed the project. The system has been in live use since May 2010.

 

TEACHING:

University-level Computer Science courses taught:

 

University-level Information Systems courses taught:

 

Miscellaneous University-level courses taught:

 

 

Professional Activities:

I have been involved with the following research conferences in the role of advisory member.

 

I have served as a reviewer for the following journals.