CV-NSF'99 · Web viewKausik Majumdar Fulbright Fellowship, ISI, Chennai, India (2004-2005) Amaury...

CURRICULUM VITAE

ROBERT KOZMA, Ph.D.

First Tennessee University Professor Department of Mathematical Sciences, 373 Dunn HallDirector, Center for Intelligent Optimization & Networks (CLION)University of Memphis, Memphis, TN 38152Cell: 626-484-7036 / Office : 901-678-2497Fax : 901-678-2480Email: [email protected]: http://clion.memphis.edu

Curriculum Vitae 1 Dr. Robert Kozma

http://clion.memphis.edu/

mailto:[email protected]

DEGREE HISTORY

1992 Ph.D. in Applied PhysicsDelft University of Technology, The Netherlands

1988 M.Sc. in Applied Mathematics (with Honors) Eotvos University, Budapest, Hungary

1982 M.Sc. in Power Engineering (with Distinction)Moscow Institute of Power Engineering, Russia, Soviet Union

PROFESSIONAL EXPERIENCE

2009 – Present Professor of Mathematical Sciences, University of MemphisDirector, CLION – Center for Large-Scale Integration Optimization & Networks

Visiting Positions: 2012 – Consultant, US Air Force Research Laboratory,

Wright Patterson Air Force Base, Dayton, OH 2008-2011 – Visiting Professor, US Air Force Research

Laboratory, Sensors Directorate, Electromagnetic Scattering Branch, Hanscom Air Force Base, MA

2006-2008 – NRC Senior Research Fellow (Summer), US Air Force Research Laboratory, Sensors Directorate, Hanscom AFB, MA

2006, Spring – Visiting Professor, Lawrence Berkeley Laboratory (LBL), UC Berkeley, CA

2005, Fall –Consultant, Sarnoff Corp., Princeton, MA 2005, Summer – Visiting professor, NASA Jet Propulsion

Laboratory, California Institute of Technology, Pasadena, CA

2005 – 2009 Professor of Computer Science, University of MemphisDepartment of Computer Science

2003 – 2005 Professor of Mathematical Sciences, University of MemphisDivision of Computer Science, Dept. Mathematical Sciences


2000 – 2003 Associate Professor, University of Memphis, Dept. of Mathematical Sciences, Division of Computer Science, and Institute for Intelligent Systems

1998 – 2000 Associate and Assist Researcher, University of California at Berkeley, joint appointment at Division of Neurobiology and Division Computer Science, Dept. EECE

1996 – 1998 Lecturer, University of Otago, Dunedin, New Zealand, Department of Information Sciences

1993 – 1996 Associate Professor, Tohoku University, Sendai, JapanDept. of Quantum Science and Engineering

1993 Spring Visiting Researcher, Tohoku University, Sendai, Japan Graduate School of Engineering

1988 – 1993 Research Fellow, Delft University of Technology, Delft, The Netherlands, Department of Applied Physics, Interfaculty Reactor Institute

1982 – 1988 Research Assistant and Research Fellow, Central Research Institute for Physics of the Hungarian Academy of Sciences, Budapest, Hungary

TEACHING EXPERIENCE

Taught a wide range of undergraduate and graduate courses in mathematics, com-puter science and engineering. Introduced new courses are marked by (*).

Undergraduate Measurements & Instrumentation Tohoku UniversityIntelligent Information Systems Otago UniversityIntroduction to Algorithms University of MemphisAdvanced Data Structures University of MemphisSoft Computing (*) University of Memphis

Graduate Soft Computing in Engineering (*) Tohoku University Neural Networks and Fuzzy


Systems Tohoku UniversityAdvanced Algorithms University of MemphisTopics in Algorithms University of MemphisCognitive Science Seminar University of MemphisNeural Networks University of MemphisComputational Intelligence (*) University of MemphisComputational Neurodynamics (*) University of MemphisReproducing Kernel Hilbert Spaces (*) University of Memphis Math-ematical Learning Theory (*) University of MemphisStochastic Optimization & Adaptive Dynamic Programming University of MemphisIntelligent Prediction (*) University of MemphisDecision Support Systems (*) University of Memphis

MENTORING POSTDOCS/ VISITING PROFESSORS

Miklos Ruszinko Renyi Institute of Mathematics, Hungarian Academy of Sciences, Budapest, Hungary (2015)

Yusuke Uchiyama Tsukuba University, Ibaraki, Japan (2014-2015)

Sanquing Hu Hangzhou Dianzi University, Shanghai, China (2014)

Joao G. Rosa U Sao Paulo, Brazil (2013)Giovanni Pazienza Pazmany Peter University, Budapest, Hun-

gary (2011-2012)Murat Demirer Istanbul Kultur University, Turkey (2007-

2008)Kausik Majumdar Fulbright Fellowship, ISI, Chennai, India

(2004-2005)Amaury Lendasse Helsinki University, Finland (2003-04)Horatio Voicu University of Texas at Arlington, TX, USA,

(2002-03)

PHD COMMITTEE CHAIR (C) / MEMBER (M)

Yury Sokolov [C] Memphis (in progress)


Roman Ilin [C] WPAFBMark Myers [C] UT HSCMarko Puljic [C] Tulane UDerek Harter [C] Texas A&M Sergi Consul [M] U Memphis (in progress)Annita Davis [M] U MemphisAnne Warlamount [M] UC MercedRazvan Mezei [M] Lenoir-Rhyne UBalazs Montagh [M] Szombathely, HungaryJonathan Cutler [M] Montclair UAngela H. Murdock [M] Middle Tenn. UHanif Azhar [M] Montreal UArpad Kelemen [M] U MarylandSaktinil Roy [M] Athabasca USahidul Pramanik [M] UT Medical SchoolNivendita Majumdar [M] Biotech, SF Bay AreaQ.S. Liu [M, Chinese U, Hong Kong]Colin Molter [M, VUB, Brussels, Belgie]Jay Swope [M, Otago, New Zealand]JaeSoo Kim [M, Otago, New Zealand]Mike Watts [M, Otago, New Zealand]Hiroshi Furukawa [M, Tohoku, Japan]Masatake Sakuma [M, Tohoku, japan]Shoichi Saito [M, Tohoku, Japan]Djen D Djainal [M, Tohoku, Japan]Gracielle Roston [M, Tohoku, Japan]Haiko Kok [M, Delft, The Netherlands]Heike Shoonewelle [M, Delft, The Netherlands]

MASTERS CHAIR

At the University of Memphis, partial list: Srinivas Achunala, Rodrigo Silva, Igor Beli-aev, Derek Wong, Sangeeta Muthu, Sai Sudha Ganti, Asha Kalidindi, Jose Rodriguez, Roman Ilin, Ravi Kumar Kondadadi, Hima Puppala, J Santosh Ankishetty, Haizhon Li, Mark Myers, Jonathan Gomez, Prashant Ankaraju.

INVOLVEMENT IN PROFESSIONAL SOCIETIES


Institute of Electrical and Electronic Engineers (IEEE, Fellow)

International Neural Network Society (INNS, Fellow)

American Mathematical Society (AMS, Member)

Society for Industrial and Applied Mathematics (SIAM, Member)

Society for Neuroscience (SfN, Member)

EDITORIAL ACTIVITIES

Associate Editor Neural Networks (since 2009)

Associate Editor Neurocomputing (since 2006)

Area Editor New Mathematics & Natural Computation (2008-)

Associate Editor Cognitive Neurodynamics (since 2008)

Associate Editor Cognitive Systems Research (since 2009)

Editorial Board Neural Computing & Applications (since 2011)

Associate Editor Soft Computing (2009 - 12)

Associate Editor IEEE Transactions on Neural Networks (2005-09)

Guest Editor Neural Networks, special issue on “Advances in Neural Network Research” (2009)

Guest Editor New Mathematics & Natural Computation, special issue on “Neurodynamic Correlates of Higher Cognition (2009)

Guest Editor Neural Networks special issue on “Goal Directed Neural Systems” (2009)

Guest Editor International Journal of Intelligent Systems, special issue “Intentional Dynamic Systems: Fundamental Concepts and Robotics Applications” (2006)

Guest Editor IEEE Transactions on Neural Networks, special issue on “Temporal Coding for Neural Information Processing (2005)

Guest Editor Journal of Integrative Neuroscience, special issue on “Complex Nonlinear Neural Dynamics:


Experimental Advances and Theoretical Interpretations” (2003)

Guest Editor Information Sciences, special issue on “Methods and systems for intelligent human-computer interaction (2000)

Guest Editor International Journal of Intelligent Systems, special issue on “Hybrid intelligent adaptive systems (1998)

REVIEWER OF INTERNATIONAL JOURNALS

Acta Biotheoretica (Kluwer)

Autonomous Robots (Springer)

Applied Energy

Behavioral & Brain Sciences (Cambridge University Press)

Brain Research Bulletin (Elsevier)

Chaos – An Int. Journal (Inst. of Physics IOP)

Chemical Engineering & Processing (Elsevier)

Digital Signal Processing (Elsevier)

Fuzzy Sets and Systems (North Holland)

Hippocampus (Wiley)

IEEE Computational Intelligence Magazine

IEEE Transactions on Biomedical Engineering

IEEE Transactions on Computers

IEEE Transactions on Image Processing

IEEE Transactions on Systems, Man, and Cybernetics

IEEE Transactions on Evolutionary Computing

IEEE Transactions on Knowledge Discovery & Engineering

IEEE Signals Journal

Int. J. Bifurcation and Chaos (World Scientific)

Int. J. Intelligent Systems (Wiley)


Int. J. Multiphase Flow (Pergamon Press)

Information Science (Elsevier)

Journal of Advanced Computational Intelligence (Japan)

Journal of Integrative Neuroscience (World Scientific)

Journal of Theoretical Biology (Elsevier)

Neural Information Processing – Reviews (KAIST, Korea)

Neural Processing Letters (Springer)

Neuroscience (Elsevier)

Neuroscience Research (Elsevier)

Ocean Engineering (Elsevier)

Physica A (Elsevier)

Physica D (Elsevier)

Physics Letters A (Elsevier)

Physics of Life Reviews (Elsevier)

Robotics and Autonomous Systems (Elsevier)

UNIVERSITY SERVICE

Member, U of Memphis Faculty Senate, 2009-2014

Member, Faculty Senate Standing Committee of Research Policies, 2013-2014

Member, Faculty Senate Committee on Committees, 2013-2014

Member, Graduate Committee, Department MSCI, 2012-2014

Faculty Senate Standing Committee of Faculty Policies 2012-2013

Member, T & P Committee, Department MSCI, 2009-2014

Chair, Faculty Search Committee, Department CS, 2007-2008

Member, Teaching and Learning Advisor Committee, VP IT 2006-2008

Member, TAF Grant Evaluation Committee; 2006-2007

Member, Provost’s Task Force on Internationalization, 2005-2006

Member, Tenure and Promotion Appeals Committee, 2005-2006

Chair, Faculty Evaluation Committee, Department CS, 2005-2006


Member, Colloquium & Travel Committee, Department CS, 2004-2005

Chair, Space and Equipment Committee, Department CS, 2002-2005

Coordinator of Internships, Department CS, 2001-2003

Member, College of Arts & Sciences Graduate Council, 2002-2005

Member of Dean’s Ad Hoc Comm. Multidisciplinary Studies, A&S, 2003-2004

Member, Chair’s Search Committee, Department of CS, 2002-2003

Member, Graduate Studies Committee, Department CS, 2002-2005

Chair, Funding Allocation Committee, Institute for Intelligent Systems, 2001-2002

HONORS AND AWARDS

Institute of Electrical and Electronic Engineers, IEEE Fellow, 2014

International Neural Network Society, INNS Fellow, 2013

Gabor Award, International Neural Network Society, 2011

First Tennessee University Professor, since 2012

Distinguished Research Achievement Award by Alumni Association, University of Memphis, 2010

College of Arts and Sciences Distinguished Research Award, College A&S, University of Memphis, 2009

Dunavant Jr. University Professor, University of Memphis, 2009-2012

Senior Research Fellow, National Research Council (NRC), National Academies of Sciences & Engineering, 2006-2009

Patron of the Year Award, Finalist, Air Force Research Laboratory, Sensory Directorate AFRL/RY, 2007

Best Paper Award IROS2007, Runner up with T. Huntsberger, H. Aghazarian (NASA, JPL) and W.J. Freeman (UC Berkeley), IEEE Int. Conf. Robotics & Systems, San Diego, 2007

Best Paper Award DMIN06, jointly with A. Buczak (Sarnoff Co, Princeton, NJ), International Data Mining Conference, Las Vegas, 2006

MTA-SOROS Fellowship Award, New York, 1986, 1988


Higher Education Award, Ministry of Education, Budapest, Hungary, 1983

Diploma with Distinction ('red'), Moscow Energy University, Russia, 1982

1st Prize Award for Best Research Work of Graduate Students, Moscow, Russia 1982

LANGUAGES

Fluent in English, Hungarian, and Russian.Understands and speaks Dutch and basic Japanese.

PROFESSIONAL ACTIVITIES AND POSITIONS

Governor, Board of Governors, International Neural Network Society INNS, 2007-2009, 2010-2012

Fellow Committee Member, IEEE Computational Intelligence Society CIS, 2014

Advisory Committee Member, AdCom, IEEE Computational Intelligence Society CIS, 2009-2012

Chair, University Curriculum Committee, Education Committee, IEEE CIS, 2012-2013

Chair, Distinguished Lecturers Program DLP IEEE CIS, 2010-2011

Chair, Technical Committee of Standards, IEEE Computational Intelligence Society, 2008-2009

Chair, SIG Special Interest Groups, of International Neural Network Society 2005-2008

Member, Neural Networks Technical Committee IEEE Neural Networks/ Computational Intelligence Society NNTC, since 1996

CONFERENCE ORGANIZING ACTIVITIES

Publications Chair, IEEE Symposium Series on Comp. Intelligence SSCI2014, Dec, 9-12, 2014, Orlando, FL, USA.

Chair, Symposium on Independent Computing, at IEEE Symp. Series on Comp. Intelligence SSCI2014, Dec, 9-12, 2014, Orlando, FL, USA.


Symposium Co-Chair, Computational Intelligence in Brain Computer Interfaces, at IEEE Symp. Series on Comp. Intelligence SSCI2014, Dec, 9-12, 2014, Orlando, FL, USA.

Tutorial Chair: IEEE World Congress on Computational Intelligence WCCI2014/IJCNN2014, June 8-13, 2014, Beijing, China.

Financial Chair, IEEE Symp. Series on Computational. Intelligence SCCI2013, May 5-10, 2013, Singapore.

Program Co-Chair, IEEE/INNS International Joint Conference on Neural Networks (June 10-15, 2012, Brisbane, Australia.

Program Chair, 2012 International Conference on Brain Inspired Cognitive Systems, July 11-14, 2012, Zhenyang, China.

Steering Committee Co-Chair, 3nd International Conference on Aware Computing & Technology iCAST2012, August 21-24, 2012, Seoul, Korea.

Tutorial Chair, IEEE/INNS International Joint Conference on Neural Networks (July 30 – Aug 4, 2011, San Jose, CA.

General Co-Chair, 2nd International Symposium on Aware Computing (Nov. 1-4, 2010, National Cheng Kung University, Taiwan)

General Chair, IEEE/INNS International Joint Conference on Neural Networks, IJCNN09 (June 15-19, 2009, Atlanta, GA)

Program Co-Chair at IEEE World Congress on Computational Intelligence WCCI08 (June 1-6, 2008, Hong Kong)

Program Co-Chair, Conference on Brain Network Dynamics (January 26-27, 2007, Stanford-Berkeley, CA, USA)

Chair for Finances/Treasurer, IEEE World Congress of Computational Intelligence WCCI 2006 (July 16-20, 2006, Vancouver, Canada)

Program Co-Chair of NSF US-Hungarian Workshop on Large Scale Random Graphs Methods for Modeling Mesoscopic Behavior in Biological and Physical Systems, August 28 – September 4, 2006, Budapest, Hungary.

Program Co-Chair, IEEE/INNS International Joint Conference on Neural Networks IJCNN’04 (July 25-29, 2004, Budapest, Hungary);

Program Committee Co-Chair, International Conference on Neural Information Processing ICONIP'97 (November, 1997, Dunedin, New Zealand).

Program Committee member at international conferences:

- Int. Joint Conf. Neural Networks, IJCNN2014 (July 8-13, 2014, Beijing, China)


- Int. Joint Conf. Neural Networks, IJCNN2013 (Aug. 4-9, 2013, Dallas, TX)

- Cyber Security Summit, CyberSci2013 (June 25-26, 2013, Arlington, VA)

- Int. Joint Conf. Neur. Networks IJCNN201 (July 30 – Aug. 4, 2011, San Jose, CA)

- Int. Conf. Systems, Man, and Cybern. SMC 2011 (Oct. 2011, Anchorage, Alaska)

- Int. Conf. Intelligence and Intelligent Informatics IWACIII2011 (Nov. 19-23, 2011, Suzhou, China)

- Int. Conf. Cognitive Neurodynamics ICCN09 (November 15-19, 2009, Zhejiang U, Hangzhou, China)

- Int. Workshop on Aware Computing IWAC09 (September 18-20, 2009, Aizu Wakamatsu, Japan)

- 2009 Int. Symp. Learning & Adaptive Behavior in Robotic Systems (July 22-24, 2009, Iasi, Romania)

- Symp. Comp. Intelligence for Security and Defense Appl. CISDA (July 8-10, 2009, Ottawa, Canada)

- Int. Conf. on Simulation of Adaptive Behavior SAB08 (July 7-12, 2008, Osaka, Japan)

- Int. Symp. Learning & Adaptive Behavior in Robotic Systems (Aug. 6-8, 2008, Edinburgh, Scotland)

- International Conference on Cognitive Neurodynamics ICCN07 (Nov. 17-21, 2007, Shanghai, China)

- Artificial Neural Networks in Engineering Conference ANNIE07 (Nov. 11-14, 2007, St. Louis, MO)

- Int. Joint Conf. Neural Networks IJCNN’07 (Aug. 12-17, 2007, Orlando, FL),

- Cognitive Science Conference CogSci’07 (Aug.1-4, 2007, Nashville, TN)

- IEEE Systems, Man, and Cybernetics Conf. SMC’05 (October 8-11, 2006, Taipei, Taiwan)

- International Symp. on Artificial Brain with Emotion & Learning (Aug. 24-25, 2006, Seoul, Korea)

- Cognitive Science Conference CogSci’06 (July 26-29, 2006, Vancouver, Canada)

- Int. Joint Conf. Neural Networks IJCNN’05 (July 31-Aug.4, 2005, Montreal, Canada),

- IEEE Int. Conf. On Fuzzy Systems FUZZ-IEEE 2005 (May 22-25, 2005, Reno, NV)


- IEEE Systems, Man, and Cybernetics Conf. SMC’05 (October 10-12, 2005, Hawaii),

- 2004 Symposium on Intentional Dynamic Systems IDS04 (April 24-26, 2004, Memphis, TN)

- Int. Joint Conf. Neural Networks, IJCNN'03 (July 14-19, 2003, Portland, OR),

- IEEE Int. Conf. On Fuzzy Systems FUZZ-IEEE 2003 (May 28-30, 2003, St. Louis, MO);

- Int. Joint Conf. Neural Networks, IJCNN'02 (May 11-15, 2002, Honolulu, HI);

- Int. Joint Conf. Neural Networks, IJCNN'01 (July 14-19, 2001, Washington DC);

- Int. Joint Conf. Neural Networks, IJCNN'99 (July 10-16, 1999, Washington DC);

- North American Fuzzy Information Processing Soc. NAFIPS'99 (June 11-13, 1999, New York);

- IEEE Int. Conf. Systems, Man and Cybernetics, SMC'97 (October 1997, Orlando, FL);

CONSULTING

Kozmos Research Laboratories LLC, Memphis, 2013 – Present

US Air Force Research Laboratory, Sensors Directorate, HAFB, MA, 2006-2008

NASA Jet Propulsion Laboratory, Pasadena, CA, 2005

Sarnoff Corporation, Princeton, NJ, 2005

PATENT DISCLOSURES

“Methods of detection of propagating phase gradients using model field theory of non-Gaussian mixtures,” US Patent, Co-Inventors, Kozma, R., L. Perlovsky, 2012. US Patent # 8,195,580.

“Integrated wireless radar system for surveillance and tracking of moving targets,” Co-Inventors, Kozma, R., L. Wang, K. Iftekharuddin, R. Deming, U.S. Patent Appl. #13/726,920, 2013.

"Methods of improved learning in simultaneous recurrent neural networks." Inventors: Kozma, R., and P. J. Werbos. U.S. Patent Appl. # 12/156,164, 2009.


BOOKS AND EDITED VOLUMES

“Cognition as a transient neuropercolation process – A complex systems perspective,” R. Kozma and W.J. Freeman, Springer Verlag, Heidelberg, (revised, 2015).

“Advances in Neuromorphic Memristor Science and Applications,” Kozma, R., R. Pino, and G. Pazienza (Eds), Springer Verlag, Heidelberg, Germany (2012).

“Handbook of Large-Scale Random Networks,” B. Bollobas, Kozma, R., D. Miklos (Eds) Bolyai Society Mathematical Studies, Springer Verlag, New York, ISBN: 978-3-540-69394-9, (2009).

“Neural Networks. 2009. Proceedings of International Joint Conference on Neural Networks IJCNN2009,” Kozma, R., S. Bressler, L. Perlovsky, K. Venayagamoorthy (Eds) ISBN 978-1-4244-3548-7, pp. 1-3541, IEEE Press, Piscataway, NJ (2009).

“Neurodynamics of Higher-Level Cognition and Consciousness,” L. Perlovsky, Kozma, R., (Eds), in Springer Series: Understanding Complexity, Springer Verlag, Heidelberg, Germany, ISBN 978-3-540-73266-2 (2007).

“Neuro-Fuzzy Techniques for Intelligent Information Processing,” Kasabov, N., Kozma R., (Eds) in Series: Studies in Fuzziness and Soft Computing, 480 p., ISBN-3-7908-1187-4, Springer Verlag, Heidelberg (1999).

“Progress in Connectionist-based Information Systems,” Kasabov, N., Kozma, R., Ko, K., O’Shea, R., Coghill, G., Gedeon, T., (Eds) Vol. 1-2, pp.1355, Springer Verlag (1997).

“Noise Investigations on Boiling Effects in a Simulated MTR-Type Fuel Assembly,” Kozma, R., Delft University Press, ISBN-90-73861-04-7 (1992).

BOOK CHAPTERS

1. Kozma, R. (2015) “Synchrony, Oscillations, and Chaos in Neural Networks,” in: “Handbook of Computational Intelligence,” J. Kacpzyk, W. Pedrycz (Eds.), Springer (in press).

2. Siegelman, H., R. Kozma (2014) “Associative Learning,” in UNESCO Encyclope-dia of Life Support Systems (EOLSS), Vol. “Computational Intelligence,” Ed. H. Ishibuchi, UNESCO EOLSS Press, New York (in press).


3. Resconi, G., & Kozma, R. (2014). Geometric Synchronization by Multi-pendu-lum and Electronic Models of Neurodynamics. In Computational Intelligence, III, pp. 247-261. Springer Series Studies in Computational Intelligence, 577, DOI 10.1007/978-3-319-11271-8_16.

4. Kozma, R. (2014). Metastable Activity Patterns in Cortical Dynamics and the Il-lusion of Localized Representations. Advances in Cognitive Neurodynamics, 4, pp. 503-507. Springer, Netherlands.

5. Kozma, R., & Freeman, W. J. (2014). Modeling Cortical Singularities During the Cognitive Cycle Using Random Graph Theory. Advances in Cognitive Neurody-namics, 4, pp. 137-142. Springer Netherlands.

6. Freeman, W. J., Kozma, R., Li, G., Quiroga, R. Q., Vitiello, G., & Zhang, T. (2015). Advanced Models of Cortical Dynamics in Perception. Advances in Cognitive Neurodynamics, 4, pp. 127-136. Springer Netherlands.

7. Kozma, R. (2014) “Neuropercolation and Neural Population Models,” in Ency-clopedia of Computational Neuroscience, R. Jung and D. Jaeger (Eds.), DOI 10.1007/978-1-4614-7320-6_71-1, Springer Verlag, New York.

8. Kozma, R. (2014) “Neural Mass Action,” in Encyclopedia of Computational Neu-roscience, R. Jung & D. Jaeger (Eds.), DOI 10.1007/978-1-4614-7320-6_68-3, Springer Verlag, New York.

9. Kozma, R., M. Puljic, W.J. Freeman (2014) “Thermodynamic Model of Criticality in the Cortex based on EEG/ECoG data,” in “Criticality in Neural Systems,” D. Plenz (Ed.), http://arxiv.org/abs/1206.1108 , pp. 153-176, John Wiley & Sons.

10. Kozma, R., R. Pino, G. Pazienza (2012) “Are Memristors the Future of AI? – Re-view of Recent Progress and Future Perspectives,” in “Advances in Neuromor-phic Memristor Science and Applications,” Kozma, R., R. Pino, and G. Pazienza (Eds), Springer Verlag, Heidelberg, Germany.

11. Freeman, W.J., Kozma, R., with app: B. Bollobas, O. Riordan (2009) “Scale-free Cortical Planar Graphs,” “ Handbook of Large-Scale Random Networks,” B. Bollobas, Kozma, R., D. Miklos (Eds) Bolyai-Springer Series on Advanced Combinatorics, Springer Verlag, New York, 2009.

12. Kozma, R. (2007) “Neurodynamics of Intentional behavior Generation,” In: Neurodynamics and Higher-Level Cognition and Consciousness, Kozma, R., L. Perlovsky (Eds), Springer Verlag, Heidelberg, Germany, ISBN: 978-3-540-73266-2, pp. 129-159.


http://arxiv.org/abs/1206.1108

13. Huntsberger, T., Tunstel, E., Kozma, R. (2006) “Onboard learning strategies for planetary surface rovers,” Chapter 20 in: Intelligence for Space Robotics, A. Howard, E.Tunstel (eds). TCI Press, San Antonio, TX, pp. 403-422.

14. Kelemen, A., Liang, Y., Kozma, R., Franklin, S. (2002) "Optimizing Intelligent Agents’ Constraint Satisfaction with Neural Networks," In: Innovations in Intelligent Systems (A. Abraham & B. Nath, Eds.), Springer Series "Studies in Fuzziness and Soft computing," Springer Verlag, Heidelberg, Germany, pp. 255-272.

15. Kozma, R., Kasabov, N. (1999) "Generic neuro-fuzzy-chaos methodologies and techniques for intelligent time-series analysis," in: Ribeiro, R., Yager, R., Zimmermann, H-J., Kacprzyk, J. (eds) Soft Computing in Financial Engineering, Physica-Verlag / Springer, Heidelberg, ISBN 3-7908-1173-4, pp. 125-141.

16. Kasabov, N., Kozma, R et al. (1999) "Hybrid connectionist-based methods and systems for speech data analysis and phoneme-based speech recognition," In: Neuro-Fuzzy Techniques for Intelligent Information Processing, N. Kasabov and R.Kozma, eds., Physica Springer Verlag, Heidelberg, pp. 241-263.

17. Kasabov, N., and Kozma, R., (1998) "Multi-scale analysis of time series based on a neuro-fuzzy-chaos methodology applied to financial data," in A. Refenes, A.N. Burgess, J.E. Moody (eds), Decision Technologies for Computational Finance, Kluwer Academic, ISBN 0-7923-8308-7.

18. Kozma, R., Kasabov, N. (1997) "Chaos and Fractal Analysis of Irregular Time Series Embedded into a Connectionist Structure," in: S-I. Amari, N. Kasabov (eds) Brain-like Computing and Intelligent Information Systems, Springer Verlag, pp. 213-237.

19. Kasabov, N., Kozma, R. (1997) "Neuro-fuzzy-chaos engineering for building intelligent adaptive information systems," in: Da Ruan (ed), Intelligent Systems: Fuzzy Logic, Neural Networks and Genetic Algorithms, Kluwer Acad. Publ., pp. 209-230.

REFERRED PUBLICATIONS - JOURNAL ARTICLES

1. Kozma, R., & Puljic, M. (2015). Random graph theory and neuropercolation for modeling brain oscillations at criticality. Current Opinion in Neurobiology, 31, 181-188. http://www.ncbi.nlm.nih.gov/pubmed/25460075


http://www.ncbi.nlm.nih.gov/pubmed/25460075

2. Rabinovich, M.I., Sokolov, Y., R. Kozma (2014) “Robust sequential working memory recall in heterogeneous cognitive networks,” Frontiers in Systems Neuroscience, 8, 220. http://www.ncbi.nlm.nih.gov/pubmed/25452717

3. Sokolov, Y., Kozma, R., Werbos, L. D., & Werbos, P. J. (2015) “Complete stability analysis of a heuristic ADP control design,” Automatica, http://arxiv.org/abs/1308.3282 (accepted, in press).

4. Davis, J.J., G. Gillett, R. Kozma (2015) “Revisiting Brentano on Consciousness: A striking correlation with ECoG findings about the Action-Perception Cycle and the Emergence of Knowledge and Meaning,” Mind and Matter (accepted, in press).

5. Hu, S., Wang, H., Zhang, J., Kong, W., Cao, Y., Kozma, R. (2015) “Causality from Cz to C3/C4 or between C3 and C4 Revealed by Granger Causality and New Causality during Motor Imagery,” IEEE Trans. Neur. Networks (accepted, in press).

6. Freeman, W.J., Capolupo, A., Kozma, R., Olivares del Campo, Giuseppe Vitiello, G.A. (2015) “Bessel Functions in Mass Action Modeling of Memories and Re-membrances,” Phys. Lett. A. (accepted, in press)

7. Kozma, R. & M. Puljic (2015) “Neuropercolation model of pattern-based com-puting in brains through cognitive phase transitions,” Theoretical Computer Science C – Natural Computing (revised)

8. Jansen, S., R. Kozma, R. Miklos, Y. Sokolov (2015) “Activation process on a long-range percolation graph with power law long edge distribution,” (in progress)

9. Hu, S., Sokolov, Y., Kozma, R., Ohl, F., Schultz, A., Wanger, T. (2015) “Causality Flow in Auditory Cortex during Gerbil Category Learning,” (in progress)

10. Kozma, R., J.J. Davis, W.J. Freeman, C.T. Lin (2015) “Spatio-Temporal EEG Pat-tern Extraction Using High-Density Arrays,” J. Neurosci. Methods (in progress)

11. Ilin, R., J. Zhang, L. Perlovsky, R. Kozma (2014) “Vague-to-Crisp Dynamics of Percept Formation Modeled as Operant (Selectionist) Process,” Cogn. Neuro-dyn. 8(1), 71-80. http://www.ncbi.nlm.nih.gov/pubmed/24465287

12. Kozma, R., M. Puljic (2013) “Learning effects in neural oscillators,” Cognitive Comp., 5(2), 164-169. http://link.springer.com/article/10.1007/s12559-012-9182-z#page-1

13. Kozma, R., Puljic, M. (2013) “Hierarchical Random Cellular Neural Networks for System-Level Brain-Like Signal Processing,” Neural Networks, 45, pp. 201-110. http://www.ncbi.nlm.nih.gov/pubmed/23548329

14. Kozma, R., Alippi, C. (2013). Nurturing the Future of Computational Intelli-gence - CIS University Curriculum Subcommittee Report. Computational Intelli-gence Magazine, IEEE, 8(3), 4-6.

15. Kozma, R. (2013) “Mathematical Theories of Physical Intelligence - Comment on Dissipation of dark energy by cortex in knowledge retrieval," by Capolupo, Freeman, and Vitiello.,” Physics of Life Reviews, 10(1), pp. 110-111. http://




http://link.springer.com/article/10.1007/s12559-012-9182-z#page-1

http://link.springer.com/article/10.1007/s12559-012-9182-z#page-1





www.ncbi.nlm.nih.gov/pubmed/23506947

16. Khan, MMR, Iftekharuddin, K., McCracken, E., Islam, K., Wang, L., Kozma, R. (2013) “Autonomous wireless radar sensor mote for target material classifica-tion,” Digital Signal Processing, 23(3), 722-735, 2013.

17. Kozma, R., J.J.J. Davis, W.J. Freeman (2012) “Synchronization of De-Synchro-nization Events Demonstrate Large-Scale Cortical Singularities As Hallmarks of Higher Cognitive Activity,” J. Neuroscience and Neuro-Engineering JNSNE, 1(1), 13-23, 2012. https://escholarship.org/uc/item/9ht4t9d6

18. Werbos, L., Kozma, R., R. L. Silva, G. Pazienza, P.J. Werbos (2012) “Metamodel-ing and Critic-Based Approach to Multi-Level Optimization,” Neur. Netw., 32, 179-185 (2012). http://www.ncbi.nlm.nih.gov/pubmed/22386785

19. Kozma, R., L. Wang, K. Iftekharuddin, E. McCracken, E. I. Khan, M., S. Bhurtel, and R.M. Demirer, R.M. (2011) “Radar-Enabled Collaborative Sensor Network Integrating COTS Technology for Surveillance and Tracking,” Special Issue on Collaborative Sensor Networks, Sensors, 12(2), 1335-1351. http://www.ncbi.nlm.nih.gov/pubmed/22438713

20. Warlaumont, A., Oller, K., Buder, E., Dale, R., Kozma R. (2010) "Data-driven au-tomated acoustic analysis of human infant vocalizations using neural network tools," J. Acoustical Soc. of America, 127(4), 2563-2577, 2010. http://www.ncbi.nlm.nih.gov/pubmed/20370038

21. Puljic, M., Kozma, R. (2010) “Broad-Band Oscillations by Probabilistic Cellular Automata,“ J. of Cellular Automata 5(6): 491-507, 2010.

22. Kozma, R. (2010) “Phase transitions and singular space-time dynamics in cognitive processing,” Phys. of Life Reviews, 7(2), pp. 262-263, 2010. http://www.ncbi.nlm.nih.gov/pubmed/20452297

23. Kozma R. (2010) “Complementary aspects of emotions and music,” Phys. of Life Rev., 7(1), pp. 41-43, 2010. http://www.ncbi.nlm.nih.gov/pubmed/20374923

24. Kozma, R., M. Puljic, L. Perlovsky (2009) “Modeling Goal-Oriented Decision Making Through Cognitive Phase Transitions,” New Math. & Natural Comp., 5(1), pp. 143-157.

25. Kozma, R., J. Caulfield (2009) “Neurodynamic Correlates of Higher Cognition and Consciousness,” New Math. & Natural Comp. 5(1), pp. 1-6.

26. Kozma, R., S. Bressler, L. Perlovsky, G.K. Venayagamoorthy (2009) “Advances in neural network research: An introduction.” Neural Networks, 22(5-6), pp., 489-490.

27. Kozma, R., W.J. Freeman (2009) “The KIV Model of Intentional Dynamics and Decision Making,” Neural Networks, 22(3), pp. 277-285.

28. Kozma, R., D. Levine, L. Perlovsky (2009) “Introduction to the special issue on goal directed neural systems,” Neural Networks, 22(3), pp. 197-199.









https://escholarship.org/uc/item/9ht4t9d6


29. Freeman, W.J., Kozma, R. (2009) “Brain neural activity patterns yielding numbers are operators, not representations,“ Behavioral & Brain Sciences, 32, pp. 336-337.

30. Kozma, R., W.J. Freeman (2008) “Intermittent spatio-temporal desynchronization and sequenced synchrony in ECoG signals,” J Chaos, 18, 037131.

31. Kozma, R., T. Huntsberger, H. Aghazarian, E. Tunstel, R. Ilin, WJ Freeman (2008) “Intentional Control for Planetary Rover SRR2k,” Advanced Robotics, Vol. 21, No. 8, pp. 1109-1127.

32. Puljic, M., Kozma, R. (2008) “Narrow-band oscillations in probabilistic cellular automata,: Phys. Rev. E. 78026214.

33. Ilin, R., Kozma, R., and P. J. Werbos (2008) "Beyond Backpropagation and Feedforward Models: a Practical Training Tool for a More Efficient Universal Approximator", IEEE Trans. Neur. Netw., 19(3), 929-937.

34. Kozma, R. (2007) “Intentional systems: Review of neurodynamics, modeling, and robotics implementations,” Physics of Life Reviews, 5(1), pp. 1-21.

35. Beliaev, I., Kozma, R. (2007) “Time series prediction using chaotic neural networks: Case study of CATS Benchmark test,” Neurocomputing, 70(13), pp. 2426-2439.

36. Kozma, R., Harter, D., Achunala, S. (2007) “Dynamical Aspects of Behavior Generation Under Constraints,” J. Cognitive Neurodynamics, 1(3), pp. 213-223.

37. Kozma, R., H. Aghazarian, T. Huntsberger, E, Tunstel, W.J. Freeman (2007) “Computational Aspects of Cognition and Consciousness in Intelligent Devices,” IEEE Comp. Intellig. Mag., 2(3), pp. 53-64.

38. Kozma, R. (2007) “Neuropercolation,” Scholarpedia, 2(8), 1360.

39. Kozma, R., Fukuda, T. (2006) “Intentional Dynamic Systems: Fundamental Concepts and Robotics Applications,” Int. J. Intelligent Systems, 21, 875-879.

40. Harter, D., Kozma, R., (2006) “Aperiodic Dynamics and the Self-Organization of Cognitive Maps in Autonomous Agents,” Int. J. Intelligent Systems, 21(9), 955-972.

41. Ilin, R., Kozma, R. (2006) “Stability of coupled excitatory-inhibitory neural populations & application to control multistable systems,” Phys. Lett. A, 360, 66-83.

42. Balister, P, Bollobas, B, Kozma, R, (2006) "Mean field models of probabilistic cellular automata", Random Structures and Algorithms, 29, 399-415.

43. Kozma, R., Puljic, M., Bollobas, B., Balister, P., Freeman, W.J. (2005) “Phase Transitions in the Neuropercolation Model of Neural Populations with Mixed Local and Non-Local Interactions,” Biol. Cybernetics, 92(6), 367-379.


44. Harter, D., Kozma, R. (2005) “Chaotic Neurodynamics for Autonomous Agents,” IEEE Trans. Neural Networks, 16(4), pp. 565-579.

45. Puljic, M., Kozma, R. (2005) “Activation Clustering in Neural and Social Networks,” Complexity, 10(4), 42-50.

46. Kozma, R., Wong, D., Demirer, M., Freeman, W.J. (2005) “Learning intentional behavior in the K-model of the amygdala and enthorhinal cortex with the cortico-hippocampal formation,” Neurocomputing, 65-66, pp. 23-30.

47. Kozma, R., M. Puljic, P. Balister, B. Bollobas, W.J. Freeman, (2004) ”Neuropercolation: A Random Cellular Automata Approach to Spatio-Temporal Neurodynamics,” Lecture Notes in Computer Science, vol. 3305, pp. 435-443.

48. Wang, D.L., Freeman, W.J., Kozma, R., Lozowski, A.G., Minai, A.A. (2004) “Guest Editorial – Special Issue on Temporal Coding for Neural Information Processing,” IEEE Trans. Neur. Netw., 15(5), pp. 953-956.

49. Kozma, R., Wong, D., Freeman, W.J., Erdi, P. (2004) “Learning environmental clues in the KIV model of the cortico-hippocampal formation,” Neurocomputing, 58-60, 721-728.

50. Voicu, H., Kozma, R., Wong, D., Freeman, W.J. (2004) “Spatial navigation model based on chaotic attractor networks,” Connection Science, 16(1), pp. 1-19.

51. Kozma, R., (2003) On the Constructive Role of Noise in Stabilizing Itinerant Trajectories on Chaotic Dynamical Systems, Chaos, Special Issue on Chaotic Itinerancy, 11(3), pp. 1078-1090.

52. Andras, P., Kozma, R., Erdi, P. (2003) “Complex Nonlinear Neural Dynamics: Experimental Advances and Theoretical Interpretations,” Journal of Integrative Neuroscience, 2(1), pp. 1-3.

53. Kozma, R., Freeman, W.J. (2003) Basic Principles of the KIV Model and its application to the Navigation Problem, Journal of Integrative Neuroscience, 2(1), pp. 125-146.

54. Kozma, R., Freeman, W.J., Erdi, P. (2003) The KIV Model – Nonlinear Spatio-temporal Dynamics of the Primordial Vertebrate Forebrain, Neurocomputing, 52-54, pp. 819-826.

55. Roy, P.K., Kozma, R., Majumdar, D.D. (2002) "From Neurocomputation to Immunocomputation: A Model and Algorithm for Fluctuation-Induced Phase Transition in Biological Systems," IEEE Transactions in Evolutionary Computation, 6(3): 292-305.

56. Kozma, R., Freeman, W.J. (2002) Classification of EEG Patterns Using Nonlinear Neurodynamics and Chaos, Neurocomputing, 44-46, pp. 1107-1112.

57. Roy, P.K., Kozma, R. (2002) “A neurocomputational approach to neuro-oncology: programmed multi-modal therapy and neuroimaging brain tumors,” Int. J. of Cancer, 91-91, Suppl. 13.


58. Kozma, R., Freeman, W.J. (2001). "Chaotic Resonance - Methods and Applications for Robust Classification of Noisy and Variable Patterns," Int. J. Bifurcation & Chaos, Vol. 11, No. 6, pp. 1607-1629.

59. Kozma, R., M. Alvarado, L.J. Rogers, B. Lau, W.J., Freeman (2001) "Emergence of un-correlated common-mode oscillations in the sensory cortex," Neurocomputing, 38-40, pp. 747-755.

60. Freeman, W.J., Kozma, R., Werbos, P.J. (2001) "Biocomplexity - Adaptive behavior in complex stochastic systems," BioSystems, 59, pp. 109-123.

61. Kozma, R. (2001) "Fragmented attractor boundaries in the KIII model of sensory information processing — Evidence of Cantor encoding in cognitive processes," Behavioral and Brain Sciences, 24(5): 820-821.

62. Freeman, W.J. and Kozma, R. (2000) "Local-global interactions and the role of mesoscopic (intermediate-range) elements in brain dynamics," Behavioral and Brain Sciences, 23(3): 401.

63. Kasabov., N., J.S. Kim, Kozma, R., T. Cohen (2001) “Rule extraction from fuzzy neural networks FuNN: method and real world applications,” J. Adv. Comp. Intelligence & Intelligent Informatics, 5(4), 193-200.

64. Kasabov, N. and Kozma, R. (2000) "Methods and systems for intelligent human-computer interaction," Special Issue in: Information Sciences, 123(1-2), pp. 1-2.

65. Kozma, R., Kasabov, N.K.; Kim, J.S.; Cohen, A. (1998) "Integration of connectionist methods and chaotic time-series analysis for the prediction of process data," International Journal of Intelligent Systems, 13(6), pp.519-38.

66. Kasabov, N.; Kozma, R. (1998) "Hybrid intelligent adaptive systems: a framework and a case study on speech recognition," International Journal of Intelligent Systems, vol.13, (no.6), p.455-66.

67. Kasabov, N., Kim, J., Kozma, R., (1998) "A fuzzy neural network for knowledge acquisition in complex time series," Control & Cybernetics, vol. 27(4), 593-611.

68. Kasabov, N., Kozma, R., Watts, M. (1998) "Phoneme-based speech recognition via fuzzy neural networks modeling and learning," Information Sciences (110) 1-2, pp.61-79.

69. Kasabov, N., Kozma, R. (1998) "Introduction: Hybrid Intelligent Adaptive Systems," International Journal of Intelligent Systems, vol.13, (no.6), pp.453-454.

70. Kasabov, N., Kozma, R. (1998) “Self-Organization and Adaptation in Intelligent Systems,” J. Adv. Comp. Intelligence, 2(6), pp. 177-178.

71. Kozma, R. (1998) "Intermediate-range coupling generates low-dimensional attractors deeply in the chaotic region of one-dimensional lattices," Physics Letters A, vol.244, (1-3), p.85-91.


72. Kozma, R., M. Kitamura, J.E. Hoogenboom (1997) Void Fraction Measurements in Nuclear Reactors via Neutron Noise Methods, Nucl. Technol., Vol. 118, 242-253.

73. Kozma, R. (1996) "Multi-Level Knowledge Representation in Neural Networks with Adaptive Structure," Int.J. Syst. Res. Inf. Sci., Vol.7., pp. 1-21.

74. Kozma, R., M. Sakuma, Y. Yokoyama, M. Kitamura (1996) "On the Accuracy of Mapping by Neural Networks Trained by Backpropagation with Forgetting ," Neurocomputing, Vol. 13, No. 2-4, pp. 295-311.

75. Kozma, R., A. Malinowski, M. Kitamura, J.M. Zurada (1996) "On Performance Measures of Artificial Neural Networks Trained by Structural Learning Algorithm," Austral. J. Intell. Information Proc. Systems, Vol.3, No. 2, pp. 10-15.

76. Konno, H., Kozma, R., M. Kitamura (1996) CML Approach to Power Reactor Dynamics I. Preservation of Normality, Annals of Nuclear Energy, Vol. 22, 119-131.

77. Kozma, R., H. Kok, M. Sakuma, D.D. Djainal, M. Kitamura (1996) "Characterization of Two- Phase Flows using Fractal Techniques, " Int. J. Multiphase Flow, Vol. 22, 953-968.

78. Sakuma, M., Kozma, R., M. Kitamura (1996) Characterization of Anomalies by Applying Methods of Fractal Analysis, Nucl. Technol., Vol. 113, No. 1, 86-99.

79. Kozma, R., M. Sakuma, S. Sato, M. Kitamura (1995) "Adaptive Neuro-Fuzzy Signal Processing System Using Structural Learning with Forgetting." Intelligent Automation and Soft Computing, Vol. 1. , No. 4, 389-404.

80. Kozma, R., S. Sato, M. Sakuma, M. Kitamura, T. Sugiyama (1995) "Generalization of Knowledge Acquired by a Reactor Core Monitoring System Based on a Neuro-Fuzzy Algorithm," Progress Nucl. Energy, Vol. 29, Nos. 3-4, 203-214.

81. Kozma, R. (1995) "Studies on the Relationship between the Statistics of Void Fraction Fluctuations and Parameters of Two-Phase Flows,’ Int. J. Multiphase Flow, Vol. 21, No. 2. 241-251.

82. Kozma, R., K. Nabeshima (1995) Studies on the Detection of Incipient Coolant Boiling in Nuclear Reactors using Artificial Neural Networks, Annals Nucl. Energy, Vol. 22, No.7 483-496.

83. Kozma, R., S. Sato, M. Sakuma, M. Kitamura (1994) Detecting Unexperienced Events via Analysis of Error Propagation in a Neuro-Fuzzy Signal Processing System, Intelligent Engng. Syst. Artif. Neur. Netw., Vol. 4, 241-246.

84. Kitamura, M., H. Furukawa, M. Sakuma, Kozma, R., T. Washio (1994) Robust Diagnosis of Nuclear Plant Anomalies Through Multiple Neuro Agent Cooperation, Trans. Am. Nucl. Soc., Vol. 70, No. 1,105-107.


85. Kozma, R., M. Kitamura, J.E. Hoogenboom, M. Sakuma (1994) Credibility of Anomaly Detection in Nuclear Reactors Using Neural Network, , Trans. Am. Nucl. Soc., Vol. 70, No. 1, 101-103.

86. Kozma, R., H. van Dam, J.E. Hoogenboom (1992) Identification of Flow Patterns by Neutron Noise Analysis During Actual Coolant Boiling in Thin Rectangular Channels, Nucl. Technol., Vol. 100, 97-110.

87. Kozma, R., J.E. Hoogenboom (1990) Flow Measurements Using Noise Signals of Axially Displaced Thermocouples, Annals of Nuclear Energy, Vol. 17, No. 9, pp. 493-513.

88. Kozma, R., J.E. Hoogenboom, H. van Dam (1990) Investigation of the Field-of-View of Neutron Detectors, Kernenergie, Vol. 33, No. 4., pp. 191-199.

89. Katona, Kozma, R. (1988) Problems of Estimation of the Thermohydraulic Parameters Using Neutron and Temperature Noise Signals, Progress in Nuclear Energy, Vol.21, 431-445.

90. Kozma, R. (1988) Application of Reactor Noise Models for the Analysis of Thermohydraulic Feedback, Progress in Nuclear Energy, Vol.21, 309-317.

91. Kozma, R., L. Mesko (1985) Independent Numerical Studies Via a Multi-Variable Coupled Neutron kinetic-Thermohydraulic Reactor Model, Progress in Nuclear Energy, Vol.15, 699-705.

92. Kozma, R. (1985) Effect of Temperature Feedback on the Neutron-Noise Field in PWRs, Annals of Nuclear Energy, Vol.12, No.5, 247-258.

93. Mesko, L., Kozma, R., (1984) Investigation of Stochastic Reactor Noise Models — A One-Variable Space-Time-Dependent Model, Nuclear Science & Engineering, Vol.88, 88-93.

REFERRED PUBLICATIONS - CONFERENCE PROCEEDINGS

90. Davis, J.J., R. Kozma, W.J. Freeman (2015) “The Art of Encephalography to

Understand and Discriminate Higher Cognitive Functions Visualizing Big Data on Brain Imaging using Brain,” INNS Int. Conf. Big Data, 8-11, Aug., 2015, San Francisco, CA.

91. Dynamics Movies Sokolov, Y., Kozma, R., “Stability of dynamic brain models in neuropercolation approximation,” Proc. IEEE Conf. Systems, Man, and Cybernetics (SMC2014), Oct. 5-8, 2014, San Diego, USA, IEEE, pp. 2230-2233.

92. Dutta, J. K., Banerjee, B., Ilin, R., & Kozma, R. (2014) “Abnormal event detection in EEG imaging-Comparing predictive and model-based approaches.” In Proc. 2014 IEEE Symposium Series SSCI2014, Computational Intelligence in Brain Computer Interfaces (CIBCI), Dec. 9-12, 2014, Orlando, USA, pp. 10-15. IEEE.


93. Davis, J.J.J., Kozma, R. (2014) “Sensitivity analysis of Hilbert transform with band-pass FIR filters for robust brain computer interfaces,” in Proc. 2014 IEEE Symposium Series SSCI2014, Computational Intelligence in Brain Computer Interfaces (CIBCI), Dec. 9-12, 2014, Orlando, USA, pp. 16-21, IEEE.

94. Myers, M.H., Kozma, R., Ilin, R., Davis, J.J.J. (2014) “Phase Cone Detection Optimization in EEG Data,” Proc. IEEE World Congress Comp. Intelligence (WCCI2014), 6-11, July, 2014, Beijing, China, pp. 2504-2511, IEEE Press.

95. Kozma, R., Freeman, W. J. (2014). “On Neural Substrates of Cognition: Theory, experiments and application in brain computer interfaces.” In Biomedical Science and Engineering Center Conference (BSEC), 2014 Annual Oak Ridge National Laboratory (pp. 1-4). DOI 10.1109/BSEC.2014.6867749, IEEE Press.

96. Sokolov, Y., Kozma, R., Rabinovich, M.I. (2014). “Noise effects in a dynamic model of attentional switching.” In Biomedical Science and Engineering Center Conference (BSEC), 2014 Annual Oak Ridge National Laboratory (pp. 1-4). DOI 10.1109/BSEC.2014.6867748, IEEE Press.

97. Kozma, R., Davis, J.J.J., Freeman, W.J., (2013) “Neurophysiological evidence of the cognitive cycle and the emergence of awareness,” Int. Conf. Awareness Sci. & Tech. (iCAST2013), pp. 149-157, Nov. 1-5, 2013, Aizu-Wakamatsu, Japan, IEEE Press.

98. Kozma, R., Sokolov, Y. (2013) “Improved Stability Criteria of ADP Control for Efficient Context-Aware Decision Support Systems,” Int. Conf. Awareness Sci. & Tech. (iCAST2013), pp. 41-46, Nov. 1-5, 2013, Aizu-Wakamatsu, Japan, IEEE Press.

99. Erdi, P., Kozma, R., Puljic, M., Szente, J. (2013) “Neuropercolation and Related Models of Criticalities.” In Contents XXIX-th Eur. Meeting of Statisticians, Hungary, Aug, 2013, pp. 106.

100. Davis, J.J.J., Kozma, R. (2013) “Creation of Knowledge & Meaning Manifested via Cortical Singularities in Cognition,” IEEE Symp. Series on Comp. Intelligence SSCI2013, Singapore, April 15-19, 2013, pp. 15-22, IEEE Press.

101. Kozma, R., Freeman, W.J. (2013) “Modeling cortical singularities during the cognitive cycle using random graph theory.” Proc. Int. Conf. Cognitive Neurodynamics (ICCN2013), Sigtuna, Sweden, June 20-25, 2013, Springer Verlag (in press).

102. Kozma, R. (2013) “Metastable activity patterns in cortical dynamics and the illusion of localized representations.” Proc. Int. Conf. Cognitive Neurodynamics (ICCN2013), Sigtuna, Sweden, June 20-25, 2013, Springer Verlag (in press).


103. Freeman, W.J., Kozma, R., Li, G., Quiroga, Q.R., Vitiello, G., Zhang, T. (2013) “Advanced models of cortical processing in perception.” Proc. Int. Conf. Cognitive Neurodynamics (ICCN2013), Sigtuna, Sweden, June 20-25, 2013, Springer Verlag (in press).

104. Kozma, R. (2013) “The race to new mathematics of brains and computers,” Proc. IEEE/INNS Int. Conf. Neur. Networks IJCNN2013, Aug. 4-9, 2013, Dallas, TX, USA, pp. 21-23, IEEE Press, 2013.

105. Kozma, R., Ilin, R. (2013) “Detection of Spatiotemporal Phase Patterns in ECoG Using Adaptive Mixture Models,” Proc. IEEE/INNS Int. Conf. Neur. Networks IJCNN2013, Aug. 4-9, Dallas, TX, USA, pp. 1290-1296, IEEE Press.

106. Kozma, R., Rosa, J., Piazentin, D. (2013) “Cognitive Clustering Algorithm for Efficient Cybersecurity Applications,” Proc. IEEE/INNS Int. Conf. Neur. Networks IJCNN2013, Aug. 4-9, Dallas, TX, USA, pp. 471-478, IEEE Press.

107. Myers, M., Joure, C., Johnston, C., Canales, A., Padmanabha, A., Kozma R. (2013) “Spatial Alignment of Scalp EEG Activity during Cognitive Tasks,” Proc. IEEE/INNS Int. Conf. Neur. Networks IJCNN2013, Aug. 4-9, Dallas, TX, USA, pp. 1197-1204, IEEE Press.

108. Myers, M. H., & Kozma, R. (2013). “Modeling Dynamics of the Human Limbic System.” In Advances in Cognitive Neurodynamics (III) (pp. 233-239), Springer, Netherlands.

109. Consul, S., Morshed, B. I., & Kozma, R. (2013). “Hardware efficient seizure prediction algorithm,” In Proc. SPIE Smart Structures and Materials+ Nondestructive Evaluation and Health Monitoring (pp. 86911J-86911J). International Society for Optics and Photonics.

110. Resconi, G., Kozma, R. (2012) “Geometry of intentionality in neurodynamics,” Inf. Conf. on Adv. Cogn. Technologies COGNITIVE2012, France, July 27-27, pp. 107-114, 2012.

111. Hossain, G., M. Myers, Kozma, R. (2012) “Study of Phase Relationships in ECoG Signals Using Hilbert-Huang Transforms,” Int. Conf. on Brain-Inspired Cogn. Systems ISNN/BICS2012, Zhenyang, China, July 11-14, 2012, Lecture Notes in Artificial Intelligence LNAI vol. 7366, pp. 174-182, Springer, 2012.

112. Kozma, R., J.J.J. Davis (2012) “On the Invariance of Cortical Synchronization Measures Across a Broad Range of Frequencies,” Inf. Conf. Awareness Sci. & Technology iCAST2012, Seoul, Korea, pp. 280-285, 2012.


113. Freeman, W.J., Kozma, R., G. Vitiello (2012) “Adaptation of the Generalized Carnot Cycle to Describe Thermodynamics of Cerebral Cortex,” Proc. IEEE World Congress Comp. Intellig. WCCI/IJCNN 2012, Brisbane, Australia, June 10-15, 2012, IEEE Press, pp. 3229-3236.

114. Davis, JJ. Joshua, Kozma, R. (2012) “Analysis of Phase Relationship in ECoG using Hilbert Transform and Information Theoretic Measures,” Proc. IEEE World Congress Comp. Intellig. WCCI/IJCNN2012, Brisbane, Australia, June 10-15, 2012, IEEE Press, pp. 887-893.

115. Ilin, R., Kozma, R. (2012) “Cognitively Motivated Learning of Categorical Data with Modeling Field Theory,” Proc. IEEE World Congress Comp. Intellig. WCCI/IJCNN2012, Brisbane, Australia, June 10-15, 2012, IEEE Press.

116. Kozma, R., T. Tanigawa, O. Furxhi, S. Consul (2012) “Autonomous decision support in heterogeneous sensor networks,” Proc. SPIE, 8408-21, pp. 1-9 (2012).

117. Kozma, R. M. Myers (2011) “Modeling Normal/Epileptic Brain Dynamics with Potential Application in Titration Therapy,” with M. Myers, in Proc. Int. Joint. Conf. Neural Networks IJCNN2011, July 30 – Aug. 4, 2011, San Jose, CA, IEEE Press.

118. Pazienza, G., Kozma, R., J. Jardis (2011) “Cellular Neural Networks and Memristors,” in Proc. Int. Joint. Conf. Neural Networks IJCNN2011, July 30 – Aug. 4, 2011, San Jose, CA, IEEE Press.

119. Werbos, L.D., Kozma, R., R. L. Silva, G. Pazienza, P.J. Werbos (2011) “Metamodeling for Large-Scale Optimization Tasks Based on Object Networks,” in Proc. Int. Joint. Conf. Neural Networks IJCNN2011, July 30 – Aug. 4, 2011, San Jose, CA, IEEE Press.

120. Ilin, R., J. Zhang, L. Perlovsky, Kozma, R. (2011)“Dynamic Logic for Vague-to-Crisp Perception and Dynamics of Operant (Selectionist) Learning,” Int. Conf. Cognitive Neurodynamics ICCN2011, June 9-13, 2011, Niseko, Hokkaido, Japan.

121. Myers, M., Kozma, R. (2013) ”Modeling Dynamics of the Human Limbic System,” In Advances in Cognitive Neurodynamics (III) pp. 233-239). Springer Netherlands.


122. Kozma, R., & Puljic, M. (2011). Metastability of Mean Field Neuropercolation–The Role of Inhibitory Populations. In Advances in Cognitive Neurodynamics (II) (pp. 41-46). Springer Netherlands.

123. Kozma, R. (2011) “Neural Correlates of Awareness in Brains and in Man-Made Devices,” 3rd Int. Conf. Awareness Science & Technology, iCAST2011, Dalian, China, September 27-30, 2011, pp. 516-520, IEEE Press.

124. Kozma, R., M. Puljic (2011) “Neural Population Dynamics Modeled by Mean Field Graphs,” Int. Conf. Numerical Analysis and Applied Mathematics ICNAAM2011, Sept. 19-25, 2011, Halkidiki, Greece, Vol. 1389, p. 1348. AIP Press.

125. Pazienza, G., Kozma R. (2011) “Memristor as an archetype of dynamic data-driven systems and applications to sensor networks,” Proc. Int. Conf. Comp. Science (ICCS) on the Ascent of Computational Excellence, Procedia Computer Science, 4, pp. 1782-1787, 2011.

126. Iftekharuddin, K., Khan, M.M.R., McCracken, E., Wang, L., Kozma, R. (2011) “Autonomous wireless radar sensor mote integrating a Doppler radar into a sensor mote and its application in surveillance and target material classification,: Proc. SPIE, Vol. 8134, 813403.

127. Kozma, R., Ilin, R. (2010) “Optimization via Efficient Learning in CNNs” Proc. IEEE Int. Conf. on Cellular Nanoscale Networks and Applications, CNNA2010, Berkeley, CA, Febr. 2-4, 2010, IEEE press.

128. Kozma, R., L. Wang, K. Iftekharuddin, E. McCracken, et al., (2010) “Multi-modal sensor system integrating COTS technology for surveillance and tracking,” IEEE Int. Radar Conf., RADAR2010, Arlington, VA, May 11-14, 2010 IEEE Press.

129. Kozma, R., Puljic, M. (2010) “Chaotic behavior in stochastic cellular neural networks,” IEEE 2010 Int. Joint Conf. Neural Networks, IJCNN2010, World Congress on Comp. Intell. WCCI2010, Barcelona, Spain, July 18-23, 2010, IEEE Press.

130. Kozma, R. (2009) “Metastability of Mean Field Neuropercolation–The Role of Inhibitory Populations,” ICCN09, Nov. 15-19, 2009, Hangzhou, China.

131. Kozma, R., Freeman, W.J. (2009) “Neurodynamics of Cognition and Consciousness,” ACM Workshop on Performance Metrics for Intelligent Systems


(PERMIS), September 21-23, 2009, 2004, National Institute of Standards and Technology. NIST, Gaithersburg, Maryland, USA, pp. 147-148, ACM Press.

132. Ilin, R., Kozma, R. (2009) “Sensor integration in KIV brain model for decision making,” Proc. Int. J. Conf. Neur. Netw., IJCNN09, 1328-1334, IEEE Press.

133. Demirer, R.M., Kozma, R., M. Caglar, Y. Polatoglu (2009) “A new nonlinear filter for the detection of phase transitions in EcoG data,” Proc. Int. J. Conf. Neur. Netw., IJCNN09, 671-676, IEEE press.

134. Myers, M., Kozma, R. (2009) “Seizure Prediction through Dynamic Synchronization Measures of Neural Populations,” Proc. Int. J. Conf. Neur. Netw., IJCNN09, 2195-2201, IEEE press.

135. Puppala, H., Kozma, R. (2008) “Identification of phase transitions in simulated EEF signals,” Proc. Int. J. Conf. Neur. Netw., IJCNN08, 3511-3517, IEEE press.

136. Kozma, R., L. Perlovsky, S, J. Ankishetty (2008) “Detection of propagating phase gradients in EEG signals using model field theory of non-Gaussian mixtures,”, Proc. Int. J. Conf. Neur. Netw., IJCNN08, 3524-3529, IEEE press.

137. Kozma, R., T. Huntsberger, H. Aghazarian, W.J. Freeman (2007) “Implementing intentional robotics principles using SRR2K platform,” Proc. IEEE/RSJ int. Conf. on Intelligent Robots and Systems IROS07, San Diego, Ca, Oct. 29-Nov. 2, 2007, pp. 2262-2267. Runner-up for Best Paper Award of IROS07.

138. Myers, M., Kozma, R. (2007) “Modeling Brain Electrical Activity Involving Vagus Nerve Stimulation,” Proc. Int. Conf. Artificial Neural Networks in Engineering ANNIE2007, November 11-14, 2007, St. Louis, MO. Intelligent Engineering Systems Through Artificial Neural Networks, Vol. 17, pp. 3-8. ASME Press.

139. Rodriguez, J., Kozma, R. (2007) “Phase Synchronization in Mesoscopic Electroencephalogram Arrays.” Proc. Int. Conf. Artificial Neural Networks in Engineering ANNIE2007, November 11-14, 2007, St. Louis, MO. Intelligent Engineering Systems Through Artificial Neural Networks, Vol. 17, pp. 9-14. ASME Press.

140. Myers M.H., Kozma R, W.J. Freeman (2007) "Studies in Synchronization using KIV Model", .Proceedings. International Conference on Cognitive Neurodynamics '07, November, 2007, China. Advances in Cognitive


Neurodynamics ICCN07, R. Wang et al. (eds), Vol. II, pp. 207-211, Springer Verlag, 2008

141. Kozma, R., R. Deming, L. Perlovsky (2007) “Estimation of Propagating Phase Transients in EEG Data -Application of Dynamic Logic Neural Modeling Approach,” Proc. International Joint Conference on Neural Networks, IJCNN'07, Aug. 10-14, 2007, Orlando, FL, pp. 1602-1606.

142. Linnehan, R., J. Schindler, D. Brady, Kozma, R., R. Deming, L. Perlovsky (2007) “Resolving Wall Ambiguities Using Angular Diverse Synthetic Arrays,” Proc. International Joint Conference on Neural Networks, IJCNN'07, Aug. 10-14, 2007, Orlando, FL, pp. 1721-1726.

143. Ilin, R., Kozma, R. (2007) "Control of multi-stable chaotic neural networks using input constraints", Proc. International Joint Conference on Neural Networks, IJCNN'07, Aug. 10-14, 2007, Orlando, FL, pp. 1558-1563.

144. Kozma. R., Puljic, M. (2007) "Modeling Scale-free neurodynamics using neuropercolation approach," Proc. 6th Int. Congress of Industrial and Applied Mathematics, ICIAM07, 16-20, July, 2007, Zurich, Switzerland, PAMM Proc. Applied Mathematics & Mechanics, Wiley, Vol. 7, pp. 1122001-1122002.

145. Kozma, R. Perlovsky, R. Deming (2007) “Optimal Estimation of Parameters of Transient Mixture Processes Using Dynamic Logic Approach,” Proc. Integration of Knowledge Intensive Multi-Agent Systems KIMAS 2007. , April 30-May 3, 2007, Waltham, MA, IEEE press, pp. 1-6.

146. Kozma, R., R. Linnehan, L. Perlovsky, D. Brady, John Schindler, (2007) Target Localization Behind Walls Using Dynamic Logic-Based Autofocusing Approach, IEEE 2007 Radar Conference, April 17-20, 2007, Waltham, MA, pp. 850-855.

147. Ilin, R., Kozma, R., P. Werbos (2007) “Efficient Learning in Cellular Simultaneous Recurrent Neural Networks - The Case of Maze Navigation Problem,” IEEE Int. Symp. Approx. Dyn. Prog. & Reinforcement Learning, April 2007, Honolulu, Hawaii, IEEE Press, pp. 324-329.

148. Kozma, R., (2006) “Influence of Criticality on 1/f^a Spectral Characteristics of Cortical Neuron Populations,” Proc. IEEE World Congress on Computational Intelligence, July 16-21, 2006, Vancouver, Canada, IEEE Press, pp. 632-637, 2006.


149. Ilin, R., Kozma, R., P.J. Werbos (2006) “Cellular SRN trained by extended Kalman filter shows promise for ADP,” Proc. IEEE World Congress on Computational Intelligence, July 16-21, 2006, Vancouver, Canada, IEEE Press, 506-510, 2006.

150. Beliaev, Kozma, R., (2006) “Studies on the memory capacity and robustness of chaotic dynamic neural networks,” Proc. IEEE World Congress on Computational Intelligence, July 16-21, 2006, Vancouver, Canada, IEEE Press, 3991-3998, 2006.

151. Majumdar, K.K., Kozma, R. (2006) “Studies on Sparse Array Cortical Modeling and Memory Cognition Duality,” Proc. IEEE World Congress on Computational Intelligence, July 16-21, 2006, Vancouver, Canada, IEEE Press, 4964-4967, 2006.

152. Kozma, R., Buczak, A. (2006) “Biomedical Hypothesis Generation & Testing by Evolutionary Computation ,“ Proc. Int. Conference on Data Mining DMIN’06, Eds. S. Crone et al., Recipient of Best Paper Award, June, 2006, Las Vegas, CSREA Press, 97-106.

153. Kozma, R., M. Puljic (2006) “Noise-Mediated Intermittent Synchronization of Collective Behaviors in the Probabilistic Cellular Automata Model of Neural Populations,” 10th Artificial Life Conference ALIFEX, June 3-7, 2006, Bloomington, IN, MIT Press, pp. 310-316.

154. Kozma, R., Tunstel, E. (2005) “A novel approach to distributed sensory networks using biologically-inspired sensory fusion,” IEEE 2005 Syst. Man, & Cyb. Conf., October 2005, Hawaii, Vol. 2, 1005-010.

155. Beliaev, I., Ilin, R., & Kozma, R. (2005) “Nonlinear neurodynamics tool for system analysis and application for time series prediction,” IEEE 2005 Systems, Man and Cybernetics Conf. Hawaii, Vol. 2, pp. 1011-1016.

156. Kozma, R., Myers, M. (2005) “Analysis of phase transitions in KIV with amygdala during simulated navigation control,” IEEE/INNS Joint Conference on Neural Networks IJCNN’05, July 30-Aug. 5, 2005, Montreal, Canada, pp. 125-130.

157. Ilin, R., Kozma, R. (2005) ”Stability Conditions of the full KII Model of Excitatory and Inhibitory Neural Populations,” IEEE/INNS Joint Conference on Neural Networks IJCNN’05, July 30-Aug. 5, 2005, Montreal, Canada, pp. 3162-3167.

158. Azhar, H., Iftekharuddin, K., Kozma, R. (2005) “A Chaos Synchronization-Based Dynamic Vision Model for Image Segmentation,” IEEE/INNS Joint Conference


on Neural Networks IJCNN’05, July 30-Aug. 5, 2005, Montreal, Canada, pp. 3375-3380.

159. Wong, D., Myers, M., Kozma, R., Thirumalainambi, R. (2005) “Intentional navigation and phase transition analysis in amygdale of KIV model,” SAE 2005 Transactions Journal of Aerospace, 2005-01-3381, SAE International Publ., pp. 1227-1232.

160. Wong, D., Kozma, R., Tunstel, E., Freeman, W.J. (2004) “Navigation in a Challenging Martian Environment Using Multi-Sensory Fusion in KIV Model,” Proc. IEEE Int. Conf. Robotics & Automation ICRA’04, April 28 – May 1, 2004, New Orleans, LA, IEEE Press, pp. 672-677.

161. Harter, D, Kozma, R. (2004). “Aperiodic Dynamics for Appetitive/Aversive Behavior in Autonomous Agents,” Proc.IEEE Int. Conf. Robotics & Automation ICRA’04, April 28 – May 1, 2004, New Orleans, LA, IEEE Press, pp. 2147-2152.

162. Harter, D., Kozma, R. (2004) “Aperiodic Dynamics and the Self-Organization of Cognitive Maps in Autonomous Agents,” Proc. 17th Int. FLAIRS Conference, Eds. V. Barr, Z. Markov, May 17-19, 2004, Miami Beach, FL, AAAI Press, ISBN 1-57735-201-7.

163. Harter, D., Kozma, R. (2004) “Navigation and Cognitive Map Formation using Aperiodic Neurodynamics,” Proc. 8th Int. Conf.: From Animals to Animats - Simulation of Adaptive Behavior SAB'04, July 13-17, 2004, Los Angeles, CA, The MIT Press, Bradford Book, pp. 264-273.

164. Kozma, R. (2004) “On noise-induced resonances in neurodynamic models ,” IEEE/INNS 2004 Int. Joint Conference on Neural Networks IJCNN’04, July 25-29, 2004, Budapest, Hungary, IEEE Press, Piscataway, NJ, pp. 3041-3045.

165. Muthu, S., Kozma, R., Freeman, W.J. (2004) “Applying KIV Dynamic Neural Network Model for Real Time Navigation by Mobile Robot Aibo,” IEEE/INNS 2004 Int. Joint Conference on Neural Networks IJCNN’04, July 25-29, 2004, Budapest, Hungary, IEEE Press, Piscataway, NJ, pp. 1617-1622.

166. Ilin, R., Kozma, R., Freeman, W.J. (2004) “Studies on the Conditions of Limit Cycle Oscillations in the KII Models of Neural Populations,” IEEE/INNS 2004 Int. Joint Conference on Neural Networks IJCNN’04, July 25-29, 2004, Budapest, Hungary, IEEE Press, Piscataway, NJ, pp. 1511-1517.


167. Beliaev, I., Kozma, R. (2004) “Time series prediction using chaotic neural networks: Case study of IJCNN CATS benchmark test,” IEEE/INNS 2004 Int. Joint Conference on Neural Networks IJCNN’04, July 25-29, 2004, Budapest, Hungary, IEEE Press, Piscataway, NJ, pp. 1609-1613.

168. Lendasse, A. , G. Simon , Kozma, R. , V. Wertz , M. Verleysen (2004) Fast Bootstrap for Least-square Support Vector Machines, 12th European Symp. Neural Networks, ESANN 2004, Brugge, Belgium, April 28-30, 2004, pp. 525-530.

169. Kozma, R., Wong, D., Tunstel, E., Freeman, W.J. (2004) “The role of amygdala on the behavior of intentional autonomous agents,” 1st Intelligent Systems Technical Conference of the American Institute of Aeronautics and Astr. AIAA.

170. Gomez, J. Kozma, R. (2004) “Fuzzy Class Binarization using Coupled Map Lattices,” North American Fuzzy Information Processing Conference NAFIPS’04 , June 27-30, 2004, Banff, Alberta, Canada, IEEE Press, pp. 973-978.

171. Harter, D. and Kozma, R. (2004). Complex Systems Approaches to the Ontogenetic Development of Behavior.” 1st Intelligent Systems Technical Conference of the American Institute of Aeronautics and Astronautics AIAA.

172. Kozma, R., Muthu, S. (2004) “Implementing Reinforcement Learning in the Chaotic KIV Model using Mobile Robot Aibo,” 2004 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems IROS’04, Sept. 28 – Oct. 2, 2004, Sendai, Japan, IEEE Press, pp. 2337-2342.

173. Parra, C. A., K. Iftekharuddin, and R. Kozma. "Automated Brain Tumor segmentation and pattern recognition using ANN." Computational Intelligence Robotics and Autonomous Systems (2003).

174. Kozma, R., Voicu, H., Wong, D., Freeman, W.J. (2003) “A Dynamical Neural Network Algorithm for Autonomous Learning and Navigation Control,” IEEE 2003 International Conference on Systems, Man, & Cybernetics SMC'03, Washington D.C., Oct. 5-8, 2003, IEEE Press, pp. 2132-2137.

175. Kozma, R., Ankaraju, P. (2003) Learning Spatial Navigation Using Chaotic Neural Network Model, International Joint Conference on Neural Networks IJCNN’2003, Portland, OR, July 14-19, 2003, pp. 1476-1479.


176. Li, H., Kozma, R. (2003) A Dynamical Neural Network Method for Time Series Prediction Using the KIII Model, International Joint Conference on Neural Networks IJCNN’2003, Portland, OR, July 14-19, 2003, pp. 347-352.

177. Puljic, M., Kozma, R. (2003) Phase Transitions in a Probabilistic Cellular Neural Network Model Having Local and Remote Connections, International Joint Conference on Neural Networks IJCNN’2003, Portland, OR, July 14-19, 2003, pp. 831-835.

178. Kozma, R., Li, H., Freeman, W.J. (2003) “Learning environmental clues in the KIV model,” Computational Neuroscience Conference CNS*2003, July 4-9, 2003, Alicante, Spain.

179. Kozma, R., Freeman, W.J., Erdi, P. (2002) "The KIV-Model: Spatio-Temporal Dynamics of the Cortico-Hippocampal System," 2002 Computational Neuroscience Conference CNS*2002, Chicago, IL, July 21-25, 2002.

180. Harter, D., Kozma, R. (2002) "Simulating the Principles of Chaotic Neurodynamics," in the Proceedings of the 6th World Multiconference on Systemics, Cybernetics and Informatics (SCI 2002), July 15-17, 2002, Orlando, Florida, Vol. XIII, pp. 598-603.

181. Kozma, R., Harter, S., Achunala, S. (2002) "Action Selection Under Constraints: Dynamic Optimization of Behavior in Machines and Humans," International Joint Conference on Neural Networks IJCNN’02, World Congress on Computational Intelligence WCCI’2002, Honolulu, Hawaii, May 12-17, 2002, pp. 2574-2579.

182. Pramanik, S., Kozma, R., Dasgupta, D. (2002) "Dynamical Neuro-Representation of an Immune Model and its Application for Data Classification," International Joint Conference on Neural Networks IJCNN’02, World Congress on Computational Intelligence WCCI’2002, Honolulu, Hawaii, May 12-17, 2002, pp. 130-135.

183. Kozma, R., P. Balister, B. Bollobas (2002) "Self-organized development of behaviors in spatio-temporal dynamical systems," International Joint Conference on Neural Networks IJCNN’02, World Congress on Computational Intelligence WCCI’2002, Honolulu, Hawaii, May 12-17, 2002, pp.2261-2265.

184. Kozma, R., Majumdar, N.S., Dasgupta, D. (2002) "Optimum Complexity Neural Networks for Anomaly Detection Task," International Joint Conference on


Neural Networks IJCNN’02, World Congress on Computational Intelligence WCCI’2002, Honolulu, Hawaii, May 12-17, 2002, pp.1138-1142.

185. Kondadadi, R., Kozma, R. (2002) "A Modified Fuzzy ART for Soft Document Clustering," International Joint Conference on Neural Networks IJCNN’02, World Congress on Computational Intelligence WCCI’2002, Honolulu, Hawaii, May 12-17, 2002, pp. 2545-2549.

186. Kelemen, A., Kozma, R., Liang, Y. (2002) "Neuro-Fuzzy classification for the job assignment problem," International Joint Conference on Neural Networks IJCNN’02, World Congress on Computational Intelligence WCCI’2002, Honolulu, Hawaii, May 12-17, 2002, pp. 1831-1836.

187. Gonzalez, F., D. Dasgupta, Kozma, R. (2002) "Combining Negative Selection and Classification Techniques for Anomaly Detection," International Conference on Evolutionary Computation, ICEC’02, World Congress on Computational Intelligence WCCI’2002, Honolulu, Hawaii, May 12-17, 2002, pp. 705-710.

188. Garzon, M.H., P. Ankaraju, E. Drumwright and Kozma, R. (2002) "Neurofuzzy Recognition and Generation of Facial Features in Talking Heads," IEEE International Conference on Fuzzy Systems, Fuzzy-IEEE’02, World Congress on Computational Intelligence WCCI’2002, Honolulu, Hawaii, May 12-17, 2002, pp. 926-931.

189. Kozma, R., Balister, P., Bollobas, B., Freeman, W.J. (2001) "Dynamical Percolation Models of Phase Transitions in the Cortex," in: Proc. NOLTA’01 Nonlinear Theory and Applications Symposium, Miyagi, Japan, Oct. 28-Nov. 1, 2001, Vol. 1, pp. 55-59.

190. Kozma, R., Freeman, W.J. (2001) "Control of Mesoscopic/ Intermediate-Range Spatio-Temporal Chaos in the Cortex," Proc. 2001 American Control Conference ACC01, June 25-27, 2001, Arlington, VA, pp. 263-268.

191. Kozma, R., D. Harter, W. Freeman, S. Franklin (2001) "Self-Organizing Ontogenetic Development for Autonomous Adaptive Systems," IEEE/INNS Int. Joint Conf. Neural Networks, Washington D.C., July 14-19, 2001, pp. 633-637.

192. Kozma, R., W.J. Freeman (2001) "Analysis of Visual Theta Rhythm - Experimental and Theoretical Evidence of Visual Sniffing," IEEE/INNS Int. Joint Conf. Neural Networks, Washington D.C., July 14-19, 2001, pp. 1118-1123.


193. Kozma, R., W.J. Freeman (2001) "Use of nonlinear dynamics and chaos for classification of EEG patterns," Int. Conf. Computational Neuroscience CNS*2001, June 30-July 5, Asilomar, CA.

194. Harter, D., Kozma, R., Franklin, S. P. (2001) " Task environments for the dynamic development of behavior," International Conf. Computer Science ICCS/ISDA, May 28-30, 2001, San Francisco, CA; "Lecture Notes in Computer Science", Springer Verlag, LNCS 2047, pp.

195. Harter, D., Kozma, R., Graesser, A.C. (2001) "Models of ontogenetic development for autonomous adaptive systems," in: Proceedings of the 23rd Annual Conference of the Cognitive Science Society (CogSci 2001), Edinburgh, U.K., August 1-4, 2001.

196. Harter, D., Kozma, R. (2001) "Ontogenetic development of behavior for simple tasks," Proceedings of the Artificial Intelligence and Soft Computing Conference (ASC 2001), Cancun, Mexico, May, 2001, pp. 410-413.

197. Harter, D., Kozma, R., Franklin, S. P. (2001) "Ontogenetic development of skills, strategies, and goals for autonomously behaving systems ," World Conference on Systemic, Cybernetics, and Informatics, SCI’2001. July 22-25, 2001. Vol. III, pp. 178-182.

198. Kozma, R. and W.J. Freeman (2000) "Encoding and recall of noisy data as chaotic spatio-temporal memory patterns in the style of the brains," Proc. IEEE/INNS Int. Joint Conf. Neural Networks IJCNN2000, July 24-27, Como, Italy, Vol. 5, pp. 33-38.

199. Kozma, R. and W.J. Freeman (2000) "The effect of external and internal additive noise on the pattern classification performance of chaotic neural networks," Proc. Int. Conf. on Systemics, Cybernetics, & Informatics SCI2000, Orlando, Fl, July 23-26, Vol. 10, pp. 407-412.

200. Roy, P.K., Kozma, R., D. Dutta Majumdar, J. Biswas (2000) "From neuro-computing to immuno-computing: Tumor stability analysis as a new anti-cancer strategy," In: Advances in Pattern Recognition and Digital Techniques , Eds: N.R. Pal, A.K. De, J. Das, Proc. 4th Internat. Conf. Advances in Pattern Recognition and Digital Techniques, ICAPRDT'99, Calcutta, India, pp. 372-376, Narosa, London, 2000.

201. Kozma, R. and W.J. Freeman (1999) "A possible mechanism for intermittent oscillations in the KIII model of dynamic memories — the case study of


olfaction," Proc. IEEE/INNS Int. Joint Conf. Neural Networks, July 10-16, Washington D.C., Vol. 1, pp. 52-57.

202. Roy, P.K., D.D. Maiumdar, Kozma, R., J. Biswas (1999) "A cybernetic approach to spontaneous cancer remission," Proc. 11th Int. Conf. Of Cybernetics & Systems, ICCS’99, Brunel Univ., London.

203. Kozma, R., N. Kasabov (1998) "Rules of chaotic behavior extracted from a fuzzy-neural network," Proc. WCCI’98, Int. Conf. Fuzzy Systems FUZZ-IEEE, Anchorage, AK, May 5-9, 1998, Vol. 2, pp.1159-1163.

204. Kasabov, N., Kozma, R. and Duch, W. (1998) Rule extraction from linguistic rule networks and from fuzzy neural networks: propositional versus fuzzy rules, in: Proceedings of the Conference on Neural Networks and Their Applications NEURAP’98, Marseilles, France, 11-13 March (1998) 403-406.

205. Kozma, R., Kasabov, N.K., J.A. Swope, M.J.A. Williams (1997) Combining Neuro-Fuzzy and Chaos Methods for Intelligent Time Series Analysis — Case Study of Heart Rate Variability, Proc. Of the 1997 IEEE Int. Conf. On Systems, Man and Cybernetics, Orlando, October 12-15, 1997, Vol. 4, pp. 3025-3029.

206. Kozma, R., J.A. Swope, M.J.A. Williams, Kasabov, N. (1997) A multi-agent realisation of fractal analysis by fuzzy neural networks, Proc. Int. Conf. Neural Information Processing ICONIP97, Dunedin, November 24-28, 1997.

207. Kozma, R., (1997) On the Conscious and Subconscious Components of Knowledge Representation in Neural Networks, Proc. IEEE 1997 Int. Conf. Neural Networks, June 8-12, 1997, Houston, USA, IEEE Press, 1997.

208. Kasabov, N. and Kozma, R. (1997) Chaotic adaptive fuzzy neural networks and their applications for phoneme-based spoken language recognition, Proc. Of Int. Conf. Vision, Recognition, Action: Neural Models of Mind and Machines, Boston University, p. 109, 1997, May 28-31.

209. Takei, S., Kozma, R., Konno, H., Kitamura, M. (1996) Stability Studies in Physical Systems Using Coupled Map Lattice Method, Methodologies for the Conception, design, and Application of Intelligent Systems, Proc. IIZUKA96, Vol. 2, 696-699, Publ. World Scientific.

210. Roston, G., Kozma, R., M. Kitamura (1996) Monitorng the State of the Coolant in a Boiling Water Reactor, Proc. OECD Specialist Meeting on In-core


Instrumentation and Reactor Core Assessment, 1996, Mito, Japan, Oct. 16-17, 1996.

211. Kozma, R., M. Kitamura, S. Saito, (1996) Monitoring of NPP state using structural adaptation in a neural signal processing system, Proc. ANS 1996 Topical Meeting on "Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies" PennState, PA, May 6-9, 1996.

212. Kozma, R., M. Kitamura (1996) The Virtue of Partial Skeletonization in Neural Networks, Proc. IEEE 1996 Int. Conf. Neural Networks, June 3-6, 1996, Wash. D.C.,USA, Publ.: IEEE Press.

213. Ishige, T., Sato, S., Kozma, R., Kitamura (1996) Elaboration of Structural Learning for Rule Elicitation and Understanding by Neural Networks, Methodologies for the Conception, design, and Application of Intelligent Systems, Proc. IIZUKA96, Vol. 2, 941-944, Publ. World Scientific.

214. Kozma, R., H. Konno, M. Kitamura (1995) “Coupled Map Lattice Approach to the Stability of Power Reactors,” Proc. 7th OECD Symposium on Nuclear Reactor Surveillance and Diagnosis (June 19-23, 1995, Avignon, France) Ed. P. Nagel, Publ.: OECD Nucl. En. Agency, Vol. 1, 211-218.

215. Kozma, R., H. Konno, T. Sugiyama, M. Kitamura (1995) Application of Coupled Map Lattices to the Investigation of Power Oscillations in BWRs, Proc. 9th

Power Plant Dyn., Testing Symp. (May 24-26, 1995, Knoxville, TN, USA) Ed. B.R. Upadhyaya, Publ.: Univ. Tennessee, Vol. 2, 80.01-80.09.

216. Kozma, R., Kitamura, M., Malinowski, A., Zurada, J.M. (1995) On Performance Measures of Artificial Neural Networks Trained by Structural Learning Algorithms, Proc. 2nd New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, November 20-23, 1995, Dunedin, NZ, Publ. IEEE Comp. Soc. Press, pp. 22-25.

217. Kozma, R., M. Kitamura (1995) Dynamic Structure Adaptation in Feed-Forward Neural Networks — An example of Plant Monitoring , Proc. IEEE 1995 Int. Conf. Neural Networks, Nov. 27 — Dec. 1, 1995, Perth, Australia, Publ.: IEEE Press, USA, Vol. 2, 692-697.

218. Kozma, R., M. Kitamura, M. Ishikawa (1995) Selecting Optimum Neural Network Architecture Using Structural Learning Algorithm with Forgetting, Proc. 1995 Annual Conference of Japanese Neur. Network Soc. (October 18-20, 1995) Ed.: R. Futami, Publ.: JNNS, pp. 303-304.


219. Kozma, R., Y. Yokoyama, M. Kitamura (1995) Intelligent Monitoring of NPP Anomalies by and Adaptive Neuro-Fuzzy Signal Processing Methods, Proc. ANS Topic. Mtg. On Computer-Based Human Support Systems: Technology, Methods & Future (June 25-29, 1995, Philadelphia, PA, USA) Ed. A. Poucet, pp. 449-456.

220. M. Sakuma, H. Schoonewelle, Kozma, R., M. Kitamura, J.E. Hoogenboom (1995) Boiling Anomaly Detection by Various Signal Characterization Methods, Proc. 7th OECD Symp. On Nuclear Reactor Surveillance an Diagnosis (June 19-23, 1995, Avignon, France) Ed. P. Nagel, Publ.: OECD Nucl. En. Agency, Vol. 1, 391-399.

221. M. Kitamura, H. Furukawa, Kozma, R., T. Washio (1995) Guiding Rules for Development of Intelligent Monitoring System of Nuclear Power Plants , Proc. 7th OECD Symposium on Nuclear Reactor Surveillance and Diagnosis (June 19-23, 1995, Avignon, France) Ed. P. Nagel, Publ.: OECD Nucl. En. Agency, Vol. 1, 14.51-14.59.

222. M. Sakuma, Y. Yokoyama, T. Washio, Kozma, R., M. Kitamura (1995) Integrated Multi-perspective Monitoring of Incipient Anomalies in Nuclear Power Plants , Proc. 9th Power Plant Dyn., & Testing Symp. (May 24-26, 1995, Knoxville, TN, USA) Ed. B.R. Upadhyaya, Publ.: Univ. Tennessee, Vol. 2, 58.01-58.12.

223. Kozma, R., Y. Yokoyama, M. Kitamura (1995) Predictive Acquisition of Knowledge by a Hybrid NPP Monitoring System, Proc. 9th Power Plant Dyn., & Testing Symp. (May 24-26, 1995, Knoxville, TN, USA) Ed. B.R. Upadhyaya, Publ.: Univ. Tennessee, Vol. 2, 59.01-59.08.

224. Djainal, D.D., M. Sakuma, Kozma, R., M. Kitamura (1995) Characterizing Two-Phase Flow Patterns Using Fractal Techniques, Proceedings of 2nd Int. Conf. Multiphase Flow (April 3-7, 1995, Kyoto, Japan) Ed. A. Serizawa, Vol. 3 FT 1.31-1.36.

225. Kozma, R., M. Sakuma, S. Sato, M. Kitamura. (1994) Evaluating the Consistency Between Input Uncertainty and Learning Accuracy in Neural Networks, Proceedings of 3rd Int. Conf. On Fuzzy Logic, Neural Nets and Soft Computing (Aug. 3-7, 1994, Iizuka, Japan) Publ.: FLSI, Fukuoka, Japan, 69-70.

226. Kozma, R., M. Kitamura, M. Sakuma, Y. Yokoyama (1994) Anomaly Detection by Neural Network Models and Time Series Analysis, Proc. IEEE World Congress on Comput. Intelligence, IEEE International Conference on Neural Networks (June 28 — July 2, 1994, Orlando, USA) Publ.: IEEE Press, USA, Vol. 5, 3207-3210.


227. Nabeshima, K., Kozma, R., E. Turkcan (1994) Analysis of the Response Time of an On-line Boiling Monitoring System in Research Reactors with MTR-Fuel , Proc. 16th Int. Meeting on Reduced Enrichment for Research and Test Reactors (Oct., 1993, Oarai, Japan) Publ.: JAERI-M 94-042.

228. Kozma R. (1991) Interpretation of Velocities Measured by Neutron Noise in BWRs, Proc. 6th Symp. On Nuclear Reactor Surveillance and Diagnostics (May 1991, Knoxville, USA) Publ.: OECD, Paris, France, Vol. 2, 38.01-38.11.

229. Kozma, R., J.E. Hoogenboom, H. van Dam (1989) Boiling Detection Using Signals of Self-Powered Neutron Detectors and Thermocouples, Proc. Of OECD Specialists’ Meeting on In-Core Instrumentation and Reactor Core Assessment (June 1988, Cadarache, France) Publ. By OECD, Paris, France, pp.390-398.

230. Kozma, R., (1986) Analysis of Noise Phenomena Caused By Thermo-hydraulic Processes in PWRs, Proc. 6th Power Plant Dynamics, Control and Testing Symposium, April 1986, Knoxville, USA, Editors: B.R. Upadhyaya et al., Vol.1, 40.01-40.18.

231. Kozma, R. (1984) Analysis of Thermophysical Feedback Effects on the Noise Field of Nuclear Power Reactors, Proc. IAEA Seminar Diagnosis of and Response to Abnormal Occurrences at NPPs, June 1984, Dresden, G.D.R., IAEA-TECDOC-334, 479-492.

INVITED/KEYNOTE TALKS, SPECIAL SESSIONS, PANELS

Special Symposium Talk: ”Experimental Evidence of the ‘Aha’ Moment in Con-scious Experience,” Int. Conf. Towards the Science of Consciousness (TSC15), Aug. 8-13, 2015, Helsinki, Finland.

Invited Talk: Transient Spatio-Temporal Dynamics as Modus Operandi of Large-Scale Networks, Antofagasta University, December 18, 2014, Chile.

Plenary Talk: Transient Spatio-Temporal Dynamics as Modus Operandi of

Large-Scale Networks, Xth IEEE Latin-American Summer School on Computa-

tional Intelligence, Dec. 16, 2014, University of Chile, Santiago, Chile.

Featured Talk: Phase Transitions in the Auditory Cortex of Gerbils During Reinforcement Learning Indicating Strategy Change, 2014 NSF Collaborative Research on Computational Neurosciences (CRCNS) PI Meeting, October 16-18,


2014, Tempe, AZ, USA.

Invited Talk: Transient Dynamics of the Intentional Action-Prediction Cycle - Theory, Experiments & Applications, at NASA Jet Propulsion Laboratory, Division of Robot Autonomy, October 9, 2014, Pasadena, CA.

Invited Talk: Transient Cognitive Dynamics Modeled through Criticality in Brains, School of Cognitive and Information Sciences, University of California at Merced, October 21, 2014, Merced, CA.

Invited Talk: Neuropercolation Models of Cortical Neurodynamics – Interpre-tation of Transient Cognitive Dynamics, University of Massachusetts at Amherst, October 2, 2014, Amherst, MA.

Plenary Talk: Neural Substrates of Cognition - Theory, Experiments & Applica-tions in Brain Computer Interfaces, at Biomedical Science and Engineering Con-ference BSEC14, May 6-8, 2014, ORNL, TN, USA.

Invited Talk: The role of extreme events in natural phenomena: From solar flares and earthquakes to brains, Department of Risk Engineering, Tsukuba University, November 6, 2013, Japan.

Invited Talk: Critical Phase Transitions in the Cerebral Cortex as Part of the In-tentional Cognitive Cycle, Brain Science Institute, Tamagawa University, Nov. 5, 2013, Tokyo, Japan.

Keynote Talk: Emergent awareness in large-scale biological and technical net-works, Nov. 1, 2013, Opening Session the Int. Conf. Awareness Sci. & Technol-ogy, University Aizu-Wakamatsu, Japan.

Panel Organizer and Chair: Computational Intelligence and Cognition in Uni-versity Curricula, Int. Joint Conf. Neural Networks, Aug. 6, 2013, Dallas, TX, USA.

Invited talk: Criticality and noise in brains and reactors – Similarities and dif-ferences. Goteborg University, June 28, 2013, Sweden.

Invited Talk: “Metastable activity patterns in cortical dynamics and the illusion of localized representations.” At Dynamic Brain Forum, Int. Conf. Cognitive Neu-rodynamics, Sigtuna, Sweden, June 22, 2013.

Invited Plenary Talk: at Dynamic Brain Forum, September 3-6, 2012, Cardona, Spain.

Invited Talk: “Neuropercolation in Brains and in Cognition Models and Control Applications,” Tong Ji University, July 9, 2012, Shanghai, China.


Invited Talk: “Critical Behavior in Brains – EEG Experiments and Thermody-namic Models,” Hangzhou University, July 10, 2012, Hangzhou, China.

Plenary Talk: “High-Resolution Spatio-Temporal Neurodynamics – Experimen-tal Studies and Cognitive Relevance,” Neural Engineering Workshop, December 21-22, 2011, National Chiao-Tung University, Taiwan.

Plenary Talk: Neural Correlates of Awareness in Brains and in Man-Made De-vices, Int. Conf. Awareness Sci. & Technol., iCAST2011, September 27-30, 2011, Dalian, China.

Invited Talk: Intentional Neurodynamics in Animals and Implications for Build-ing Autonomous Devices,” Chinese Academy of Sciences, Institute of Automation, September 26, 2011, Beijing, China.

Invited Talk at Mini-Symposium on Neurodynamics “Neural Population Dy-namics Modeled by Mean Field Graphs,” Int. Conf. Numerical Analysis and Ap-plied Mathematics ICNAAM2011, Sept. 19-25, 2011, Halkidiki, Greece.

Tutorial: “Neuropercolation + Neurodynamics: Dynamical Memory Neural Net - works in Biological Systems and Computer Embodiments,” Inf. Joint. Conf. Neu-ral Networks IJCNN2011, with W.J. Freeman, July 30, 2011, San Jose, CA.

Plenary Talk: “Neuropercolation approach to singular space-time dynamics of cortical processes,” Int. Conference on Cognitive Neurodynamics ICCN2011, June 9-13, 2011, Niseko, Hokkaido, Japan.

Keynote Talk: “Dynamical Aspects of Awareness and Intentionality in Biological and Man-made Systems,” 2ns Int. Symp. On Aware Computing ISAC2010, Nov. 1-4, 2010, Taiwan.

Plenary Talk: “Metastability of Mean-field Neuropercolation – The Role of Inhibitory Populations,” at International Conference on Cognitive Neurodynamics ICCN09, Hangzhou, China, November 15-19, 2009.

Invited Lecturer of Short Course (1 week) on “Noise and Intelligence: Mathematical Foundations, Biological Background, and Computational Models,” Institute of Mathematics, Wroclaw University of Technology, Wroclaw, Poland, October 19-23, 2009.

Plenary Keynote Talk “Phase Transitions in Brains and Brain Models – Neural Substrates of Cognition and Awareness in Man and Machines, Aizu-Wakamatsu, Japan, September 18-19, 2009.

Invited Talk “Learning and Adaptation in Cellular Neural Networks,” Pazmany Peter University, Budapest, Hungary, September 10, 2009.


http://cnd.memphis.edu/ijcnn2011_Tut/



Invited Speaker “Neuropercolation Models of Cognitive Phase Transitions,” at Workshop on Advances in Neurodynamic Systems, Atlanta, GA, USA, June 17-18, 2009.

Invited Talk “Phase Transitions in Large-scale random graphs for cognitive modeling,” Dept. ECE, MST Missouri Science & Technology University, Rolla, MO, March 30, 2009.

Invited Talk “Intentional Systems – Neural Principles, Modeling, and Robotic Implementations,” Seminar Talk at Biomedial Engineering Dept, The U of Memphis, February 27, 2009.

Invited Speaker “Virtual Communities – Large-Scale Human-Computer networks,” NSF Workshop on Computational Intelligence & Machine Learning for Virtual Organizations,” October 24, 2008, George Mason U, Fairfax, VA.

Invited Workshop Talk: “NSF Workshop on Emerging Models and Technologies in Computing (EMT): Bio-Inspired Computing and the Biology and Computer Science Interface,” July 24-25, 2008, Princeton University, NJ.

Invited Talk “Chaotic Dynamical Neural Networks: Models and Applications,” Seminar at Dept. Mech. & Control Engng, Chinese U of Hong Kong, May 30, 2008, Hong Kong

Invited talk “Phase Transitions and the Dynamics of Cognitive Attractor Landscapes,” Parmenides Workshop by invitation only, May 22-23, 2008, Isle Elba, Italy

Plenary talk: “Mathematical Models of Metastable Brain Dynamics,” Chaos & Complex Systems Conference, May 7-10, 2008, Istanbul, Turkey.

Workshop Talk and Organizing: “Use of Mathematical Physics to Model Neural Correlates of Brain Activity,” Conference on Towards the Science of Consciousness, April 7-12, 2008, Tucson, AZ.

Plenary Speaker: “Cognitive Phase Transitions in Brains: Models and Applications,” Artificial Neural Networks in Engineering Conference ANNIE07 (November 11-14, 2007, St. Louis, MO)

Special Session Organizer: “Neurodynamics: from neurons to higher cognitive functions,” jointly with P. Andras (Newcastle), IJCNN 2007 (Aug. 12-17, 2007, Orlando, FL).

Workshop Organizer: “Nonlinear Brain Dynamics for Computational Intelligence,” 10th Joint Conference on Information Science JCIS07, July 19-24, 2007, Salt Lake City, UT.


Symposium Organizer: “Dynamical Systems Approaches in Neuroscience: Theory, Experiments, and Applications,” Symposium organized at 6th

International Congress on Industrial and Applied Mathematics ICIAM’07 (16-20, July, 2007, Zurich, Switzerland).

Panelist: “SBIR/STTR Phase I, Tools for Collaboration Panel,” NSF Industrial and Innovation Partnerships,” (February, 2007, September 2007, Arlington, VA)

Invited Talk: “Modeling Cortical Phase Transitions,” at NSF Conference on Brain Network Dynamics (January 26-27, 2007, Berkeley, CA).

Invited Talk: “Phase Transition Models of Intentional Cortical Dynamics,” Conference on Goal-Oriented Neural Systems (November 3-4 2006, Arlington, TX).

Panelist: Computer Modeling and Mathematics Panel at NSF Workshop “Large Scale Random Graphs Methods for Modeling Mesoscopic Behavior in Biological and Physical Systems,” Renyi Institute of Mathematics (August 29, 2006, Budapest, Hungary).

Special Track Organizer: "Neurodynamics of Higher-level Cognitive Behavior," jointly with Leonid Perlovsky at the IEEE 2006 World Congress on Computational Intelligence (July 16-20, 2006, Vancouver, Canada).

Workshop Organizer: “Neurodynamics Methods for Analysis and Control of Cognitive Behaviors,” jointly with A. Seth (NSI, CA) J. Tani (RIKEN, Japan) at 10th Artificial Life Conference ALIFEX (June 3-7, 2006, Bloomington, IN).

Keynote Talk: “Neuropercolation Model of Cortical Phase Transitions – Dynamics of Cognition and Intelligence,” Chaos & Complex Systems Symposium (May 12-13, 2006, Istanbul, Turkey).

Invited Talk: “Dynamical Systems Approach to Intentional Robots,” At Dept. EE & CS, UC Berkeley, BISC Berkeley Initiative on Soft Computing Seminar Series (February 28, 2006, Berkeley, CA).

Invited Talk: “Dynamical Systems and Intelligent Behavior,” at Florida Atlantic University, Complex Systems and Brain Sciences Institute (January 16, 2006, Boca Raton, FL).

Invited Talk: “SODAS – A Dynamical Systems Approach to Robot Intelligence and Autonomy Applied to Sample Return Rover SRR Platform,” at JPL Robot Autonomy Division (Sept. 15, 2005, Pasadena, CA).

Invited Talk: “Neuropercolation – Dynamical Approach to Autonomy,” Neuroscience Institute NSI Seminar (Sept. 8, 2005, La Jolla, CA).


Invited Talk: “Self-Organized Development of Autonomous Adaptive Systems,” Distinguished Lecturer at Navy Center of Applied Research in Artificial Intelligence NCARAI, Navy Research Laboratory NRL (May 9, 2005, Arlington, VA).

Special Session Organizer: “Neurodynamics and Intentional Dynamic Systems,” at IEEE Int. Conf. on Neural Networks, IJCNN’05 (August 4, 2005, Montreal, Canada).

Workshop Chair: “Nonlinear Spatio-Temporal Neural Dynamics,” at Int. conf. Computational Neuroscience CNS*2004 (Baltimore, MD, July 21, 2004).

Plenary Talk: “Nonconvergent Neural Memories for Robust Encoding of Noisy Sensory Data,” at ANNIE’2003 Conference (November 2-5, 2003, St. Louis, MO).

Invited Talk: “Biologically Inspired Computing – Past, Present, & Future,” at Institute of Complex Systems (Kalamazoo, MI, October 13, 2003).

Panelist: “Biologically Inspired Computational Models,” Discussion Panel at IJCNN’03 (July 20-24, 2003, Portland, OR).

Tutorial Speaker: “Neuropercolation: Dynamical memory neural Networks – Biological Systems and Computer Implementations,” Tutorial at IJCNN’03 with W.J. Freeman (July 14, 2003, Portland, OR).

Special Track Organizer: “Temporal Aspects of Information Encoding in NNs,” Special Track with 3 sessions, co-organizer with Deliang Wang and Ali Minai, at IJCNN'03 (July 14-19, 2003, Portland, OR).

Workshop Organizer: “Nonlinear Spatio-temporal Neurodynamics,” organized with Peter Andras and Peter Erdi at Computational Neuroscience Conference CNS*2003 (July 4-8, 2003, Alicante, Spain).

Invited Talk: “Dynamical Cognitive Principles, Models, and Implementations,” at NSF Conference on Advanced Computation Inspired By Biological Processes (April 6-8, 2003, Arlington, VA).

Special Session Organizer: “Nonlinear Neurodynamics,” co-organized with Walter Freeman, at IJCNN'02 (May 11-15, 2002, Honolulu, HI).

Panelist: "Your Method is Connectionist Too", at World Congress on Computational Intelligence WCCI'02/IJCNN'02 (May 11-15, 2002, Honolulu, HI).


Special Session Organizer: “Noisy Chaotic Neural Networks for Information Storage and Retrieval,” at IEEE Int. Joint Conference on Neural Networks IJCNN2001 (July 24-27, 2000, Como, Italy).

Panelist: “Facing up to the 'AI Problem': Neural Networks and High-level Intelligence and Cognition,” Panel at IEEE International Joint Conference on Neural Networks (July 10-16, 1999, Washington DC).

Panelist: “Grand Challenges to Neural Networks Community,” Panel at IEEE World Congress on Computational Intelligence WCCI98 (May 5-9, 1998, Anchorage, AK).

Invited Session: “Integration of Hybrid Methods for Artificially Intelligent Neural Networks,” at IEEE World Congress on Computational Intelligence (May 5-9, 1998, Anchorage, AK).

Invited Session “Hybrid Connectionist Systems for Knowledge Monitoring,” at IEEE Int. Conf. Syst. Man Cybern. SMC'97 (October 12-15, 1997, Orlando, FL).

Special Session Organizer: “Knowledge Monitoring by Neuro-Fuzzy Methods,” at IEEE Int.Conf. Neural Networks, ICNN'97 (June 8-12, 1997, Houston, TX).

Center for Large-Scale Integrated Optimization and Networks (CLION)

Dr. Kozma is the founding Director of the Center for Large Scale Integrated Optimization and Networks (CLION), established in close collaboration with CLION Co-Director Paul J. Werbos. The mission of CLION is the development of innovative solutions to large-scale networks and optimization problems in various defense and civilian applications, and in biomedical research areas. CLION aims at becoming a center of excellence in large-scale networks and ad-vanced intelligent optimization research, and facilitating the commercializa-tion of the research outputs.

CLION involves an interdisciplinary research team comprising University of Memphis faculty and students including Mathematical Sciences (MSCI), Com-puter Sciences (CS), Electrical Engineering and Computer Engineering (EECE), as well external collaborators from academia and governmental agencies. CLION provides University of Memphis students with research expertise in cutting-edge technologies, which provides them with a competitive advantage


in the job market.

SPONSORED RESEARCH

1. PI (with Co-PI F. Ohl, Leibnitz Institute of Neuroscience, Germany) US-German Collaboration on the Computational Neuroscience of Strategy Change in Cogni-tive Biological and Technical Systems, NSF-NIH Collaborative Research in Computational Neuroscience (CRCNS) DMS, $428,000, 2013-2016.

2. PI, Emergence of Near-Critical Regularity in Brain Network Dynamics, AFOSR - Mathematics & Cognition Program, $375,791, 2015-2017 [White Paper, revi-sion in progress].

3. PI, Intentional Action-Perception through Random Graph Theory, Physical In-telligence Research Thrust, Phase II DARPA DSO, $384,000, 2011-2013.

4. PI, CIEDETS - Radar Imaging of Occluded Artifacts, MAV6 Inc. $10,000 2012.

5. PI, Mathematical Models of Cognition and Decision Making [award unused], AFOSR/ Intergovernmental Personal Agreement (IPA), $139,840, 2012.

6. Director, High-Performance Imaging: Collaboration Agreement between U of Memphis and AFRL Sensors Directorate [in kind equipment support] WPAFB, Sensors Directorate, $500,000, 2011-2012.

7. PI, CLION Center for Large-Scale Integrated Optimization and Networks STC, U of Memphis, matching funds, $205,000, 2011-2013.

8. PI, First Tennessee Entrepreneurship Award, First TN Foundation, $22,500, 2011-2013.

9. PI, Distributed Sensing and Decision Systems, Solid State Scientific, NH, $95,047, 2010-2011.

10. PI, Complex Warfare Systems (CWS), FedEx Institute of Technology, $105,000, 2010-2011.

11. PI, Bionic Eye Recurrent Neural Network Training, UoM Foundation, $14,000, 2008-2009.

12. PI, Neurodynamics of Perception and Cognition, AFOSR/General Dynamics IT, $72,000, 2008-2009.

13. PI, Dynamic Logic for Information Fusion using Distributed and Multi-Modal Sensory Agents with Emergent Cognitive Behaviors, National Research Coun-cil, $83,500, 2007- 2008.


14. Co-PI (with V. Menon/Stanford and S. Bressler, Florida AU), Brain Network Dy-namics, NSF Cognitive and Behavioral, Sciences Program $49,900, 2007- 2008.

15. PI, Biologically-Inspired Control and Navigation Center of Advanced Robotics, FedEx Institute of Technology, seeding grant, $20,000, 2007-2008.

16. Co-PI (with B. Bollobas) Large Scale Random Graphs Methods for Modeling Mesoscopic Behavior in Biological and Physical Systems, NSF International Of-fice, $40,000, 2005-2007.

17. PI, A Model Field Theory Based Approach to Emergent Intelligence Through Communication of Cognitive Agents with Evolving Intentional Dynamic Behav-iors, National Research Council, with US Air Force Research Laboratory, Sen-sors Directorate, $26,500, 2006.

18. PI, Dynamical Approach to Behavior-Based Robot Control & Autonomy [funded, not used], NASA, through JPL Intelligent Robot Control Laboratory, Caltech, Pasadena, CA, $95,425, 2006-2007.

19. PI, REU: Percolation models of spatio-temporal dynamics during sensory in-duced phase transitions in the cortex, NSF, Research Experience for Under-graduates Program, $12,000, 2005-2006.

20. PI, (with Terry Huntsberger) Dynamic Approach for Robot Intelligence and Autonomy Applied to SRR Platform NASA/JPL Advanced Projects Office $22,500, 2005.

21. PI, (Co-PI B. Bollobas, P. Balister) Percolation models of spatio-temporal dy-namics during sensory-induced phase transitions in the cortex NSF, Quantum and Biologically Inspired Computing $759,053, 2002 – 2006.

22. Consulting (PI: J. Zurada) Modeling of spatial and temporal dynamics in biolog-ical olfactory systems, ONR-DEPSCOR, $240K (5% share), 2001-2004.

23. PI, (with Co-PI W.J. Freeman, and S. Franklin) SODAS: Models of Self-organiz-ing Ontogenetic Development of Autonomous Agents, NASA, Computing, Infor-mation and Communicating Technology CICT Program, Revolutionary Compu-tation Project $729,000, 2001-2004.

24. Co-Researcher (with W.J. Freeman, UCB), Use of EEG Attractor Reconstruction to Analyze Nonlinear Brain Dynamics, ONR, Cognitive and Neural Sciences, $34,000, 1999-2000.

25. Co-PI (with N. Kasabov, Otago U) Connectionist Based Intelligent Information Systems CBIIS (moved from NZ), New Zealand Foundation for Research, Sci-ence and Technology FoRST, NZD 1,440,000, 1998-2002.


CV-NSF'99 · Web viewKausik Majumdar Fulbright Fellowship, ISI, Chennai, India (2004-2005) Amaury...

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