University of North Carolina at Charlotte, USA

Professor of Department of Software and information Systems

Director of Complex Systems Institute

Email: mirsad@uncc.edu

Research fields

Complex Adaptive Systems

Machine Learning/Data Mining

Health Informatics

Cognitive Science

Creativity and Innovation

Qualifications

2009 MPA (Government), Harvard University, USA

1987 Ph.D. (Computer Science), Southern Methodist University, Dallas, USA

1981 M.S. (Computer Science), University of Banja Luka, USA

1977 B.S. (Computer Science), University of Banja Luka, USA

Publications (selected)

Books, Book Chapters, Dissertation

1. Hadzikadic, M., O'Brien, S., and Khouja, M., (Eds.), Managing Complexity: Practical Considerations in the Development and Application of ABMs to Contemporary Policy Challenges, Springer, 2013.
2. O. Brien, S, Hadzikadic, M., and Khouja, M, "Addressing Complex Challenges in an Interconnected World," in Managing Complexity: Practical Considerations in the Development and Application of ABMs to Contemporary Policy Challenges, Hadzikadic, O'Brien, and Khouja (Eds.), pp 1-7, Springer, 2013.
3. O. Brien, S, Hadzikadic, M., and Khouja, M, "Complexity: Where Does It Come From?," in Managing Complexity: Practical Considerations in the Development and Application of ABMs to Contemporary Policy Challenges, Hadzikadic, O'Brien, and Khouja (Eds.), pp 9-17, Springer, 2013.

Journals

1. Carmichael, T and Hadzikadic, M., "Emergent Features in a General Food Web Simulation: Lotka-Volterra, Gause's Law, and the Paradox of Enrichment," Advances in Complex Systems, 2013.

2. Yue Dong, Nicolas W. Chbat, Ashish Gupta, Mirsad Hadzikadic, and OgnjenGajic, Systems Modeling and Simulation Applications for Critical Care Medicine, the Annals of Intensive Care Journal, 2:18, 2012.

3. Ted Carmichael and Mirsad Hadzikadic, “Emergent Features in a General Food Web Simulation: Lotka-Volterra, Gause’s Law, and the Paradox of Enrichment,” to appear in the Advances in Complex Systems Journal.

4. Hadzikadic, M. and Carmichael, T., Complex Adaptive Systems, in Cognitive Science: An Interactive Approach, National Social Science Press, Fall of 2011.
5. Hadzikadic, M. and Sun, M., "Wisdom of Crowds in the Prisoner's Dilemma Context," in Advances in Machine Learning, Volume II, J. Koronacki et al (Eds.), Studies in Computational Intelligence, Springer, 2010.
6. Carmichael, T., Hadzikadic, M, Gajic O., Pilot Study: Agent-based Exploration of Complex Data in a Hospital Environment, accepted for presentation and publishing in the Proceedings of the Sixth International Workshop on Agents and Data Mining Interaction (ADMI’10) joint with the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS2010), Toronto, 2010.
7. Dréau, D., Stanimirov, D., Carmichael T., Hadzikadic M., "An Agent-Based Model of Solid Tumor Progression," 1st International Conference on Bioinformatics and Computational Biology, 8-10 April 2009, New Orleans.
8. Carmichael, T., Hadzikadic, M., Dreau, D., and Whitmeyer, J., "Towards a General Tool for Studying Threshold Effects Across Diverse Phenomena," in Advances in Information & Intelligent Systems, Z.W. Ras, W. Ribarsky(editors), Studies in Computational Intelligence, Springer, 2009.
9. Hadzikadic, M., Carmichael, T., and Curtin, C., Complex Adaptive Systems and Game Theory: An Unlikely Union, Complexity Journal, November, 2010.
10. Khouja, M., Hadzikadic, M., &Zaffar, M., An agent-based modeling approach for determining optimal price-rebate schemes, Simulation Modeling Practice and Theory Journal, vol. 16, No. 1, pp. 111-126, 2008.
11. Khouja, M., Hadzikadic, M., Rajagopalan, H., and Tsay, L., Applications of Agent-Based Modeling to Pricing of Reproducible Information Goods, Decision Support Systems Journal, vol. 44, issue 3, pages 725-739, February 2008.
12. Hadzikadic, M., Bohren, B.F., "Learning to Predict: INC2.5," IEEE Transactions on Knowledge and Data Engineering. Vol. 9, No. 1, 168-173, 1997.
13. Whitmeyer, J., Carmichael, T., Eichelberger, C., Hadzikadic, M., Khouja, M., Saric, A., Sun, M. "A Computer Simulation Laboratory for Social Theories," the 2008 IEEE/WIC/ACM International Conference on Intelligence Agent Technology, Sydney, Australia, December 2008.
14. Hadzikadic, Mirsad. Prediction Performance as a Function of the Representation Language in Concept Formation Systems, Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society, Bloomington, Indiana, pp. 850‑854, July 29‑August1, 1992.
15. Hadzikadic, Mirsad. Context‑Sensitive, Distributed, Variable‑Representation Category Formation, Proceedings of the Thirteenth Annual Meeting of the Cognitive Science Society, Chicago, Illinois, August 7‑10, 1991, pp. 269‑274.
16. Hadzikadic, Mirsad and Yun, David Y.Y. “Concept Formation by Incremental Conceptual Clustering, ”Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, Michigan, August 20‑25, 1989, pp. 831‑836.

International Conference Papers

1. Zheyuan Su and Mirsad Hadzikadic, “Applications of Complex Adaptive Systems in Portfolio Management,” Proceedings of the 5th World Congress on Social Simulation, Sao Paolo, Brazil, November 4-7, 2014.
2. Carissa Flocken, Ted Carmichael, and Mirsad Hadzikadic, “The Role of Uninformed Individuals in Making the Right Group Decisions,” The Computational Social Science of the Americas Conference, Santa Fe, New Mexico, September 18-21, 2012.
3. Mirsad Hadzikadic, “Understanding Human Behavior in Designing Building-Scale Sustainable Ecosystems,” Green Design Conference, Sarajevo, Bosnia-Herzegovina, September 27-30, 2012.
4. Eichelberger, C. and Hadzikadic, M., “Breaking the Box: Simulated Protein Computing,” Bionetics 2010, 5th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems, December 1-2, 2010, Boston, M.

http://cciweb.uncc.edu/~mirsad/

http://scholar.google.com/citations?user=SiFFNkgAAAAJ&hl=en&oi=ao

Last updated: 2015-7-8