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Valentina V. Sulimova |
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Citizenship: The |
Academic
History:
2010
Ph.D. Degree in Computer Science,
Computing Center of the Russian Academy of
Sciences,
Ph.D. Thesis:
Kernel Functions for analysis of symbolic sequences and signals of different
length
2003
M.S. Degree in Computer Science,
M.S. Thesis:
Algorithms of On-Line Signature Identification
2001
B.S. Degree in Computer Science,
Scientific
History:
2007, 2008 (June-August)
Visiting Scientist,
Birkbeck, University of London, Department of Computer
Science and Information Systems
Since 2003
Assistant Professor,
Lecture Courses:
Fundamentals of Programming (PASCAL, C),
Informatics,
Computational
Mathematics,
Operating Systems
2003-2006
Ph.D. Student,
2001 - Present
Research Assistant, then Researcher
Laboratory of
Data Analysis
Awards:
Diploma
of the XII All-Russian Conference on Mathematical Methods in Pattern
Recognition for the best young scientist paper,
Participation
in Scientific Grants:
2009-2011
Grant
of the Russian Foundation for Basic Research:
“Methods of learning regularization in
tasks of ordered and interrelated data analysis” (
2008-2010
Grant
of the Russian Foundation for Basic Research:
“Linear methods of different
kind information fusion for data analysis”.
2008-2009
Grant
of the Russian Foundation for Basic Research:
“Methods and instruments for
clustering and recognition of symbolic sequences of different length for
intellectual analysis of amino acid sequences in protein data bases on the
basis of probabilistic model of evolution”.
2007-2008
Grant INTAS Young Scientist PhD Fellowship
№ 06-1000014-6563
“Kernel-based pattern
recognition and clustering in sets of protein sequences” (V. Sulimova).
2006-2008
Grant
of the Russian Foundation for Basic Research:
“Methods of estimation of nonstationary dependences in data flows” (
2005-2007
Grant INTAS Research Project Nr: 04-77-7347:
“Principles of Dissimilarity-Based
Pattern Recognition in Signals, Symbolic Sequences and Images”
(CONSORTIUM: Czech Technical University in Prague, Faculty of Electrical
Engineering – Czech Republic; Institute Scientific Council
"Cybernetics" – Russia; Tula State
University – Russia; International Research and Training Centre for
Information Technologies and Systems – Ukraine; University of Surrey -
United Kingdom; Technische Universitat
Dresden – Germany)
2005-2007
Grant
of the Russian Foundation for Basic Research:
“Linear Methods for estimation of
dependences in data sets of arbitrary kind” (Computing Centre of Russian
Academy of Science, Principal Investigator Prof. V. Mottl)
2004-2005
Grant
of the Russian Foundation for Basic Research:
“Methods and Software of Pattern
Recognition in Spatial Data Sets of Seismic Explorations for Prospecting Oil
and Gas Collectors in Massive Rocks with Respect to Train Information from
Sparse Net of Wells” (Tula State University,
Principal Investigator Prof. A. Kopylov)
2002-2004
Grant of the Russian
Foundation for Basic Research:
“Methods and Algorithms of Pattern
Recognition in Absence of A Priory Known Feature Vectors of Objects”
(Computing Centre of Russian Academy of Science, Principal Investigator Prof.
V. Mottl)
Actual
Participation in Scientific Conferences:
7-th International Conference on Pattern
Recognition and Image Analysis
(
11-th, 12-th, 13-th, 14-th All-Russian
Conferences on Mathematical Methods in Pattern Recognition (
20-th, 21-th International Conference on
Intellectual Data Mining
(Alushta,
8-th IASTED Conference “Signal And Image Processing”,
International Conference on Pattern
Recognition, ICPR-2008,
5-th International Symposium on
Bioinformatics Research and Applications, ISBRA-2009,
Scientific
Interests:
Dissimilarity-based pattern recognition, signal
analysis, symbolic sequences analysis, on-line signature verification,
clustering of proteins, kernel-based methods, kernel construction, kernel and classifier fusion
Publications in
Russian:
About 13 publications
Recent
Publications in English:
- V. Mottl, O. Seredin,
V. Sulimova. Mathematically correct methods of
similarity measurement on sets of signals and symbol sequences of different
length. Pattern Recognition and Image Analysis,Vol.15,
No.1, 2005, pp.87-89.
- V. Mottl,
V. Sulimova, A. Tatarchuk. Multy-kernel approach to on-line
signature verification. Proceedings of
the Eighth IASTED International Conference on Signal and Image Processing, held August 14 – 16, 2006,
- V. Sulimova,
V. Mottl,
- Mottl V., Tatarchuk A., Sulimova V.,
Krasotkina O., and Seredin O.
Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion,
In: Proceedings of 7th
International Workshop Multiple Classifiers Systems, Prague, Czech Republic,
2007, pp. 1–12.
- V. Mottl,
M. Lange, V. Sulimova, A. Yermakov.
Signature verification based on fusion of on-line and off-line kernels. Proc. of 19-th International conference on Pattern Recognition
(ICPR 2008),
- V. Sulimova,
V. Mottl, C. Kulikowski,
- B. Mirkin,
V. Sulimova, V. Mottl. Is protein sequence data sufficient
for deriving homology groups? Extending Dayhoff’s
model to sequences. Technical Report.
- V. Sulimova,
V. Mottl, B. Mirkin,
- Tatarchuk, V.Sulimova,
D. Windridge, V. Mottl, M.
Lange, Supervised Selective Combining Pattern Recognition Modalities and Its
Application to Signature Verification by Fusing On-Line and Off-Line Kernels.
Lecture Notes in Computer Science, Springer