Vadim V. Mottl, D.Sci. Tula State University Lenin Ave. 92, 300012 Tula Russia Phone: (487-2) 35-36-37 FAX: (487-2) 33-13-05 E-mail: vmottl@yandex.ru

Academic History:

1994

D. Sci. degree, Institute of Control Problems of the Russian Academy of Sciences, Moscow.

Thesis: Markov Models and Methods of Pattern Recognition in Signals with Changing Probabilistic properties.

1979

Ph.D. degree, Institute of Control Problems of the Russian Academy of Sciences, Moscow.

Thesis: Method of Partial Approximation in the Structural Analysis of Experimental Waveforms.

1968

M.S. degree, Tula Polytechnic Institute, Department of Automation and Remote Control.

Scientific History:

Since 1994

Professor,
Tula State University, Department of Technical Cybernetics.

1979-1994

Associate Professor,
Tula State University, Department of Technical Cybernetics.

Lecture Courses: Markov Models for Signal and Image Analysis, Pattern Recognition, Probability Theory, Mathematical Systems Theory.

Research Team Leader.
Theoretical Research: Pattern recognition in signals and data fields with changing probabilistic properties, Markov methods in signal and image analysis.

Applications: Analysis of stereo images, analysis of seismic explorative data arrays, computer telephony.

1973-1979

Research Scientist,
Tula Polytechnic Institute, Department of Technical Cybernetics.

External Graduate Student
Institute of Control Sciences of the USSR Academy of Sciences, Moscow.

Research: Structural and linguistic signal analysis.

1969-1973

Teaching Assistant,
Tula Polytechnic Institute, Department of Automation and Remote Control.

Subjects: Theory of Automatic Control, Theory of Servomechanisms.

Scientific Interests:

Models for random processes and fields with changing probabilistic properties, change detection in random processes and fields, pattern recognition for signal and image analysis, image segmentation, texture analysis, stereo image analysis, analysis of geophysical exploratory data.

Publications:

About 70 scientific publications.

Some papers in English:

Mottl V.V., Muchnik I.B. Deterministic models and methods of pattern recognition on the time axis. I,II,III. Automation and Remote Control, Vol. 52, 1991, No. 3, pp. 398-407, No. 4, pp. 555-559, No. 5, pp. 719-725.

Dvoyenko S.D., Mottl V.V., Muchnik I.B. Supervised learning recognition of events in signals and experimental waveforms. IFAC/IMACS Symposium on Fault Detection, Supervision and Safety for Technical Processes - SAFEPROCESS'91. Baden-Baden, FRG, September 10-13, 1991.

Dvoyenko S.D., Mottl V.V., Muchnik I.B., Nikolsky M.N. Pattern recognition in experimental waveforms. Pattern Recognition and Image Analysis, Advances in Mathematical Theory and Applications in the USSR, Vol. 1, 1991, No. 1, pp. 87-98.

Ivanova T.O., Mottl V.V., Muchnik I.B. Estimation of parameters of hidden Markov models for noise-like signals with changing probabilistic properties. I,II. Pattern Recognition and Image Analysis, Advances in Mathematical Theory and Applications, Vol. 3, 1993, No. 2, pp. 99-112, 113-125.

Mottl V.V., Blinov A.B., Kopylov A.V., Zheltov S.Yu. Quasi-statistical approach to the problem of stereo image matching. SPIE Proceedings, 1994, Vol. 2363, pp. 50- 61.

Mottl V.V., Dvoyenko S.D. Supervised recognition of events in signals with changing probabilistic properties. IEEE Workshop on Nonlinear Signal and Image Processing. Neos Marmaras, Greece, June 20-22, 1995. Vol. 1, pp. 238-241.

V.V. Mottl, A.B. Blinov. A texture processing algorithm and its application to seismic section segmentation. The 4th Open Russian German Workshop “Pattern Recognition and Image Analysis”. Valday, Russian Federation, March 3-9, 1996, pp. 103-106.

V.V. Mottl, A.B. Blinov, A.V. Kopylov. Generalized technique for a class of image analysis problems based on tree-like qauasi-Markov models of the hidden informatioin. The 4th Open Russian German Workshop “Pattern Recognition and Image Analysis”. Valday, Russian Federation, March 3-9, 1996, pp. 107-111.

Mottl V.V., Muchnik I.B., Blinov A.B., Kopylov A.V. Hidden Tree-Like Quasi-Markov Model and Generalized Technique for a Class of Image Processing Problems. 13th International Conference on Pattern Recognition. Vienna, Austria, August 25-29, 1996. Track B, pp. 715-719.

I.B. Muchnik, and V.V. Mottl. Optimization Algorithms for Separable Functions with Tree-like Adjacency of Variables and their Application to the Analysis of Massive Data Sets. DIMACS Technical Report 97-16, April 1997. Center of Discrete Mathematics and Theoretical Computer Science. Rutgers, the State University of New Jersey, USA.

V.V. Mottl, A.B. Blinov, A.V. Kopylov, A.A. Kostin. Optimization techniques on pixel neighborhood graphs for image processing. International Workshop on Graph-Based Representations. Lyon, France, April, 17-18, 1997 (to appear).

Mottl V.V., Kostin A.A., Muchnik I.B. Generalized Edge-Preserving Smoothing for Signal Analysis. International Workshop on Nonlinear Signal and Image Analysis. Mackinac Island, Michigan, USA, September 7-11, 1997 (to appear).