Academic History:

1997

Ph.D. degree, Institute of Control Problems of the Russian Academy of Sciences, Moscow.
Thesis: Quasi-Statistical Approach to Image Matching.

1993

M.S. degree, Tula State University, Department of Automation and Remote Control.

Scientific History:

Since October 2021

Leading Researcher

Tula State University, Laboratory of cognitive technologies and simulation systems.

Associate Professor,

Tula State University, Institute of Applied Mathematics and Computer Science.

2013 - 2021

Associate Professor,

Tula State University, Institute of Applied Mathematics and Computer Science.

Lecture Courses: Image Analysis, Digital Signal Processing, Computer Graphics.

Research: Parametric procedures for edge-preserving image smoothing

2005 - 2013

Associate Professor,

Tula State University, Department of Technical Cybernetics.

Lecture Courses: Intelligent Technologies, Computer Graphics, Operating Systems, Signal and Image Processing.

Theoretical Research: Optimization approach to the image and signal analysis.

03/2008-05/2008

Visiting Researcher,

Dorodnicyn Computing Centre of Russian Academy of Sciences.

2001-2005

Postdoctoral Research Fellow,

Tula State University, Department of Technical Cybernetics.

Research: Pairwise Separable Optimization for Signal and Image Processing.

1997-2001

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

Lecture Courses: Intelligent Technologies, Automation and Control.

Researcher,
Laboratory of Data Analysis, Department of Technical Cybernetics.

Theoretical Research: Edge preserving in image smoothing, image matching and texture analysis.

Applications: Analysis of satellite photographs.

1993-1996

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

Lecture Courses: Methods of Optimization

Research: Methods and algorithms of massive data set processing based on models of random processes and fields with changing probabilistic properties.

Applications: Analysis of seismic explorative data arrays, image analysis.

1993-1990

Post Graduate Student,
Tula State University, Department of Technical Cybernetics.

Research: Analysis of stereo images.

Scientific Interests:

Data Mining, Image Processing, Image Analysis, Pattern Recognition, Machine Vision.

Recent Projects

RFBR 16-07-01039. Development of methods and algorithms for processing images and other types of ordered data on the basis of Trained Markov Models. Head of the project. Project finished in 2018

RFBR 17-07-00319 “Intelligent data analysis based on matrices of pairwise comparisons” (2017-2018), Investigator. Project finished in 2019

RFBR 18-07-01087 “Methods and algorithms of high-performance intellectual dependency estimation in big data sets”. (2018-2020), Investigator. Project finished in 2020

RFBR 18-07-00942 “Methods and algorithms for constructing mathematically correct comparison functions of binary images based on skeletons”, Investigator. Project finished in 2020

RFBR 20-07-00441 “Methods and fast algorithms for round-the-clock visibility restoration of images, obtained in real weather conditions, in the presence of haze, fine particles and localized light sources”. Head of the project. Current project.

Publications:

About 135 scientific publications.

Some papers in English:

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

• V.V. Mottl, A.V. Kopylov, A.B. Blinov, S.Yu..Zheitov. Processing stereoscopic images on the basis of random field interpolation. 5th International Workshop on Digital Image Processing and Computer Optics “Image Processing and Computer Optics”, Samara, Russia, August 22-26, 1994, pp. 2-3.

• V.V. Mottl, A.V. Kopylov, S.Yu..Zheitov. Quasi-statistical approach to the image matching. St.-Petersburg Great Lakes Conference on Digital Photogrammetry and Remote Sensing, St.-Peterburg, June 25-30, 1995, pp. 75-76.

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

• V.V. Mottl, I.B. Muchnik, A.B. Blinov, A.V. Kopylov. 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.

• V.V. Mottl, A.V. Kopylov. Algorithms for Matching Images with Raster Distortions. Pattern Recognition and Image Analysis.. Advances in Mathematical Theory and Applications. Vol. 6, 1996, No. 4, October-December.

• V.V. Mottl, I.B. Muchnik, A.B. Blinov, A.V. Kopylov. A generalized approach to a class of image processing problems based on a tree-like quasi-Markov model of neighbourhood relation between the grid elements. Pattern Recognition and Image Analysis.. Advances in Mathematical Theory and Applications. 1997, Vol. 7, No. 1.

• Mottl V.V., Blinov A.B., Kopylov A.V., Kostin A.A. Computer-aided signal and image processing: A universal variational approach. Journal of Journals: Review of Global Scientific Achievements, 1998, Vol. 2, No. 1, pp. 23-30.

• V.V. Mottl, A.A. Kostin, and A.V. Kopylov. Variational Methods for Edge Preservation in the Analysis of Signals and Images. Pattern Recognition and Image Analysis, Vol. 9, No. 2, 1999, pp 292-295.

• V.V. Mottl, A.B. Blinov, A.V. Kopylov, N. Zabyski and I.B. Muchnik. Evaluation of Apparent Motion in Dynamic Data Arrays. Pattern Recognition and Image Analysis, Vol. 11, No. 1, 2001, pp 224-227.

• Mottl, A. Kopylov, A. Kostin, A. Yermakov, J. Kittler. Elastic transformation of the image pixel grid for similarity based face identification. Proceedings of the 16th International Conference on Pattern Recognition, August 11-15, 2002, Quebec City, Canada. 

• V.V. Mottl, S.D. Dvoenko, A.V. Kopylov. Pattern Recognition in Interrelated Treelike Data Arrays. Pattern Recognition and Image Analysis, Vol. 13, No. 1, 2003, pp. 95–97.

• Kopylov. Parametric dynamic programming procedures for edge preserving in signal and image smoothing // Proceedings of the 7th International Conference on Pattern Recognition and Image Analysis, St.Petersburg October 18-23, 2004. Volume I, pp. 281-284.

• Mottl V., Dvoenko S., Kopylov A. Pattern Recognition in Interrelated Data: The Problem, Fundamental Assumptions, Recognition Algorithms. Proceedings of the 17th International Conference on Pattern Recognition, August 22-26, 2004, Cambridge, UK.  Vol.1, P 188-191.

• Dvoenko, A. Kopylov, V.Mottl. Pattern recognition in interrelated data: the problem, fundamental assumptions, recognition algorithms // Proceedings of 17th ICPR’2004, August 23-26, Cambridge, UK, vol. 1, pp. 188-191.

• Kopylov A.V. Parametric dynamic programming procedures for edge preserving in signal and image smoothing. Pattern Recognition and Image Analysis, Vol. 15, No. 1, 2005. P. 227-230.

• Kopylov A.V. Dynamic programming procedures for image analysis. Proceedings of the Eight IASTED International Conference INTELLIGENT SYSTEMS AND CONTROL, October 31 – November 2, 2005, Cambridge, USA.: ACTA Press, pp. 404-409.- 515 p.

• Karceva A., Kopylov A. Optimization Criteria for Signal and Image Smoothing Algorithms. Pattern recognition and Information Processing: Proceedings of the Ninth International Conference (22-24 may 2007, Minsk, Republic of Belarus, vol.I. – Minsk: United Institute of Informatics roblems of National Academy of Sciences of Belarus, 2007. – pp 208-212.

• Kopylov A. Acyclic pair-wise separable optimization for image processing. Pattern recognition and Information Processing: Proceedings of the Ninth International Conference (22-24 may 2007, Minsk, Republic of Belarus, vol.I. – Minsk: United Institute of Informatics problems of National Academy of Sciences of Belarus, 2007. – pp 203-207.

• Kopylov. Row-wise aggregation of variables in dynamic programming algorithm for image processing. //7th Open German/Russian Workshop on Pattern Recognition and Image Understanding. August 20—23, 2007. Ettlingen, Germany.

• P.A. Melnikov, A.V. Kopylov. Row-wise aggregation of variables in dynamic programming algorithm for image processing // PRIA-8-2007, 8th International Conference, Yoshkar-Ola, RF, October, 8-13, 2007

• A.V. Kopylov. Rowwise Aggregation of Variables in the Dynamic Programming Algorithm for Image Processing.// Pattern Recognition and Image Analysis, 2008, Vol. 18, No. 2, pp. 309–313.

• Seredin, A. Kopylov, V. Mottl, A. Pryimak. Selection of subsets of interrelated features in pattern recognition problem.// 9th International Conference “Pattern Recognition and Image Analysis: New Information Technologies” (PRIA-9-2008): Conference Proceedings. Vol. 2.- Nizhni Novgorod, 2008, pp. 151 – 154.

• A.V. Kopylov. Dynamic programming for edge-preserving smoothing in signal and image analysis and pattern recognition with interrelated features.// 9th International Conference “Pattern Recognition and Image Analysis: New Information Technologies” (PRIA-9-2008): Conference Proceedings. Vol. 1.- Nizhni Novgorod, 2008, pp. 325 – 328.

• Kopylov, “Tree-serial dynamic programming for image processing,” Proceedings of 19th International Conference on Pattern Recognition,ICPR 2008, December 8-11, Tampa, Florida, USA., 2008, pp. 1–4.

• Seredin, A. Kopylov, V. Mottl, Selection of Subsets of Ordered Features in Machine Learning // In: Petra Perner (Ed.): Machine Learning and Data Mining in Pattern Recognition, 6th International Conference, MLDM 2009, Leipzig, Germany, July 23-25, 2009. Proceedings. Lecture Notes in Computer Science 5632 Springer 2009, pp. 16-28.

• Seredin, A. Kopylov, V. Mottl, Selection of Subsets of Ordered Features in Machine Learning //Transactions on Machine Learning and Data Mining, Vol. 2, No. 2, 2009, pp. 65-79.

• Krasotkina, A. Kopylov, V. Mottl, and M. Markov. Bayesian Estimation of Time-Varying Regression with Changing Time-Volatility for Detection of Hidden Events in Non-Stationary Signals. Proceedings of the 7th IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2010), February 17-19, 2010, Innsbruck, Austria, pp. 8-15.

Andrey Kopylov, Olga Krasotkina, Oleksandr Pryimak and Vadim Mottl. A Signal Processing Algorithm Based on Parametric Dynamic Programming. Lecture Notes in Computer Science, 2010, Volume 6134/2010, 280-286.

• Fan-Chieh Cheng, Bo-Hao Chen, Shih-Chia Huang, Sy-Yen Kuo, Boris Vishnyakov, Andrei Kopylov, Yury Vizilter, Leonid Mestetskiy, Oleg Seredin, Oleg Vygolov. An automatic motion detection algorithm for transport monitoring systems // 2013 IEEE 17th Int. Symp. Consum. Electron. (ISCE), Hsinchu, Taiwan, R.O.C.: IEEE, 2013. P. 195–196.

• Cheng, Y.-J., Chen, B.-H., Huang, S.-C., Kuo, S.-Y., Kopylov, A., Seredin, O., Mestetskiy, L., Wu, C.-T.  Visibility enhancement of single hazy images using hybrid dark channel prior (2013) Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013  PP. 3627 - 3632  doi: 10.1109/SMC.2013.618.

• Larin, A., Seredin, O., Kopylov, A., Kuo, S. Y., Huang, S. C., & Chen, B. H. Parametric Representation of Objects in Color Space Using One-Class Classifiers //Machine Learning and Data Mining in Pattern Recog-nition. – Springer International Publishing, 2014. – P. 300-314.

• Pham, C. T. and Kopylov, A. V. Multi-quadratic dynamic programming procedure of edge– preserving denoising for medical images:, International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, XL-5/W6, 101-106, doi:10.5194/isprsarchives-XL-5-W6-101-2015, 2015.

• Inessa Gracheva, Andrey Kopylov and Olga Krasotkina. Fast Global Image Denoising Algorithm on the Basis of Nonstationary Gamma-Normal Statistical Model. Fourth International Conference, AIST 2015, Yekaterinburg, Russia, April 9-11, 2015, Revised Selected Papers. Communications in Computer and Information Science, Vol. 542, Springer, Р. 71-82.

• BH Chen, A Kopylov, SC Huang, O Seredin, R Karpov, SY Kuo, KR Lai, et al. Improved global motion estimation via motion vector clustering for video stabilization. //Engineering Applications of Artificial Intelligence. – 2016. – Т. 54. – С. 39-48.

• Inessa Gracheva and Andrey Kopylov. Image Processing Algorithms with Structure Transferring Properties on the Basis of Gamma-normal Model. 5th International Conference, AIST 2016, Yekaterinburg, Russia, April 7-9, 2016, Revised Selected Papers. Communications in Computer and Information Science, Vol. 661, Springer, Р. 11-122.

• Vakurin, V., Kopylov, A., Seredin, O., & Mertsalov, K. Active Learning Strategy for Text Categorization Based on Support Vectors Relative Positioning. Supplementary Proceedings of the Sixth International Conference on Analysis of Images, Social Networks and Texts (AIST 2017) Moscow, Russia, July 27 - 29, 2017, CEUR Workshop Proceedings CEUR-WS.org, Vol-1975, pp 146-155, 2017.
• Kopylov, A., Seredin, O., Kushnir, O., Gracheva, I. and Larin, A. Background-Invariant Robust Hand Detection based on Probabilistic One-Class Color Segmentation and Skeleton Matching // Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018). P. 503-510. ISBN: 978-989-758-276-9
• Shi, L. F., Chen, B. H., Huang, S. C., Larin, A., Seredin, O., Kopylov, A., & Kuo, S. Y. (2018). Removing Haze Particles from Single Image via Exponential Inference with Support Vector Data Description, IEEE Transactions on Multimedia. 2018. doi: 10.1109/TMM.2018.2807593
• Thang PC, Kopylov AV. Tree-serial parametric dynamic programming with flexible prior model for image denoising. Computer Optics 2018; 42(5): 838-845. DOI: 10.18287/2412-6179-2018-42-5-838-845
• Pham, C.T., Gamard, G., Kopylov, A., & Tran, T.T.T. An algorithm for image restoration with mixed noise using total variation regularization //Turkish Journal of Electrical Engineering & Computer Sciences. – 2018. – Т. 26. – №. 6. C. 2831-2845
• Gracheva I. A., Kopylov A. V. Tone Compression Algorithm for High Dynamic Range Medical Images //ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. – 2019. – Т. 4212. – С. 87-95
• Thao, T. T. T., Thang, P. C., Kopylov, A. V., & Van Nguyen, N. An Adaptive Variational Model for Medical Images Restoration //ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. – 2019. – Т. 4212. – С. 219-224.
• Seredin, O. S., Kopylov, A. V., Huang, S. C., & Rodionov, D. S. A Skeleton Features-Based Fall Detection Using Microsoft Kinect v2 with One Class-Classifier Outlier Removal //ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. – 2019. – Т. 4212. – С. 189-195.
• V. Vakurin, A. Kopylov, K. Mertsalov, and O. Seredin, “A multiclass words classification by the recurrent neural network with memory (LSTM) as applicable to the named entity recognition problem,” in CEUR Workshop Proceedings, 2020, vol. 2667, pp. 293–298.
• Kopylov, A., Seredin, O., Filin, A. et al. Detection of interactive voice response (IVR) in phone call records. Int J Speech Technol (2020). https://doi.org/10.1007/s10772-020-09754-3
• Larin A.O., Seredin O.S., Kopylov A.V. One-Class Classification Criterion Robust to Anomalies in Training Dataset //Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings, Part V. – Springer International Publishing, 2021. – С. 155-165.
• 128.    Gracheva, I. A. and Kopylov, A. V.: Medical images fusion algorithm based on probabilistic gamma-normal model with structure-transferring properties, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-2/W1-2021, 79–83, https://doi.org/10.5194/isprs-archives-XLIV-2-W1-2021-79-2021, 2021.
  

Major awards and honors

Best Talk Award, The 5th international conference on Analysis of Images, Social networks, and Texts AIST'2016, April 7-9, Yekaterinburg, Russia, 2016.

Best Paper Award, The Seventh IASTED International Conference on Signal Processing, Pattern Recognition and Applications, February 17 – 19, Innsbruck, Austria, 2010.

Grant for Young Teachers of the Leading Russian State Universities, Potatin Foundation, 2004.

Young Scientists Competition Winner, 5th International Conference “Pattern Recognition and Image Analysis: New Information Technologies”, Samara, Russia, October 16-22, 2000.

Award Winner, MAIK Nauka/Interperiodica Publishing Company, “For the best series of publications in journals of Russian Academy of Sciences in 1997”, 1997.

Reviewer for Conferences and Journals, Conferences Section Chair, Member of Program Committee:

• Reviewer of the Journal of Computer Optics
• Reviewer of the «IEEE Access».
• Reviewer of the «IEEE Signal Processing Letters».
• Reviewer of the «Transactions on Geoscience and Remote Sensing».
• Reviewer of the Journal of Systems Architecture
• Reviewer of the Sensing and Imaging (SSTA) journal
• Reviewer of the Journal of Machine Learning and Data Analysis
• Reviewer of the Turkish journal of electrical engineering and computer sciences
• Section chair on the 2021 International Conference on “Artificial Intelligence and Big Data in Digital Era”. 2021
• Section chair on the 3rd ISPRS International Workshop “Photogrammetric and computer vision techniques for video surveillance, biometrics and biomedicine”. 2019
• Section chair on the 7th International Symposium on Information and Communication Technology (SoICT 2016), Ho Chi Minh, Vietnam, 2016
• Section chair on the Eighth IASTED International Conference on Intelligent Systems and Control 2005
• Member of Program Committee of the 9th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2017)
• Member of Program Committee of the 4th, 5th and 6th International Conference on Analysis of Images, Social Networks, and Texts (AIST-2015, AIST-2016, AIST-2017, AIST-2018, AIST-2019)
• Member of Program Committee of the ISPRS International Workshop (PSBB13, PSBB15, PSBB17, PSBB19, PSBB21)
• Member of Program Committee of the International Symposium on Information and Communication Technology (SoICT2015, SoICT2016, SoICT2018, SoICT2019)
• Member of Program Committee of the International Conference on Computer Graphics and Vision (GraphiCon 2011, GraphiCon 2012, GraphiCon 2013, GraphiCon 2017, GraphiCon 2019)
• Member of Program Committee of the International workshop on Recent Advances in Machine Learning, Data Science, Intelligent Systems & Networking (MaDaIN’2020, MaDaIN’2021)), Danang, Vietnam. 
• Member of Program Committee ofthe International Conference on Pattern Recognition (ICPR-2012, ICPR-2014, ICPR-2016, ICPR-2018, ICPR-2020)
• Member of Program Committee ofInternational Conference on Computer Vision Theory and Applications (VISAPP-2019, VISAPP-2020, VISAPP-2021)
• Member of Publicity Team of the 2018 IEEE World Congress on Services (BIGDATA CONGRESS/CLOUD/EDGE/ICCC/ICIOT/ICWS/SCC). 

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