International Journal of Information Science

International Journal of Information Science is a peer-reviewed journal that publishes original papers of high scientific value in all areas of information science. The journal publishes high-quality, refereed articles. It emphasizes a balanced coverage of both theory and practice. It fully acknowledges and vividly promotes a breadth of the discipline of information sciences.


Lev Utkin

Editorial Board Member of International Journal of Information Science

Head of Academic Department/Faculty, Department of Industrial Control and Automation, Russia

Research Areas

Imprecise Probability Theory, Machine Learning, Decision Making, Reliability Theory

Education

2001DSc.Mathematical modelling, numerical methods and program systems. Saint-Petersburg State Institute of Technology (Technical University)
1989PhDInformation processing and control systems. Leningrad Institute of Electrical Engineering (now St. Petersburg Electrotechnical University)
1986MS Automation and telemetry. Leningrad Institute of Electrical Engineering (now St. Petersburg Electrotechnical University)

Experience

2006-PresentPro-rector for Research and the head of the Department of Industrial Control and Automation. Saint-Petersburg State Forest Technical University
2003-2006Professor. Saint-Petersburg State Forest Technical University. Department of Computer Science
2001-2003Research Fellow of the Alexander von Humboldt Foundation. Munich University, Institute of Statistics
1991-2001Associate Professor. Saint-Petersburg State Forest Technical University. Department of Computer Science
1989-1991Post-graduate student. Leningrad Institute of Electrical Engineering (now St. Petersburg State)
1986-1989Research Associate. Leningrad Institute of Electrical Engineering (now St. Petersburg State Electrotechnical University). Department of Computer-Aided Engineering and Data Processing Systems.Department of Computer-Aided Engineering and Data Processing Sys

Academic Achievement

Awarded an Alexander von Humboldt Foundation Fellowship (2001-2003)
Awarded the 1997 Prize Fellowship of the President of Russia

Membership

Member of the Executive Committee of the Society for Imprecise Probability Theory and Applications (SIPTA)

Publications: Conferences/Workshops/Symposiums/Journals/Books

[1]  Utkin L.V., Zatenko S.I. and Coolen F.P.A. (2009): Combining imprecise Bayesian and maximum likelihood estimation for reliability growth models. In: Th. Augustin, F.P.A. Coolen, S. Moral and M.C.M. Troffaes: Proc. of the Sixth Int. Symposium on Imprecise Probabilities: Theories and Applications, ISIPTA'09. pp. 421-430 SIPTA. Durham, United Kingdom.
[2]  Utkin L.V. (2009): Multi-criteria decision making with a special type of information about importance of groups of criteria. In: Th. Augustin, F.P.A. Coolen, S. Moral and M.C.M. Troffaes: Proc. of the Sixth Int. Symposium on Imprecise Probabilities: Theories and Applications, ISIPTA'09. pp. 411-420 SIPTA. Durham, United Kingdom.
[3]  Utkin L.V. (2009): A new ranking procedure by incomplete pairwise comparisons using preference subsets. Intelligent Data Analysis Vol. 13(2) pp. 229-241. A version similar to the published paper can be downloaded.)
[4]  Utkin, L.V. and Destercke, S. (2009): Computing expectations with continuous p-boxes: Univariate case, International Journal of Approximate Reasoning. 50(5) 778-798. (A version similar to the published paper can be downloaded.)
[5]  Utkin L.V. and Simanova N.V. (2008): Multi-criteria decision making by incomplete preferences. Journal of Uncertain Systems Vol. 2(4) pp. 255-266.
[6]  Utkin, L.V. (2007): Risk analysis under partial prior information and non-monotone utility functions, International Journal of Information Technology and Decision Making. 6(4) 625-647. (A version similar to the published paper can be downloaded.)
[7]  Utkin, L.V. and Augustin, Th. (2007): Decision making under incomplete data using the imprecise Dirichlet model, International Journal of Approximate Reasoning. 44(3), 322-338. (A version similar to the published paper can be downloaded.)
[8]  Utkin, L.V. (2007): Second-order uncertainty calculations by using the imprecise Dirichlet model, Intelligent Data Analysis. 11(3), 225-244. (A version similar to the published paper can be downloaded.)
[9]  Utkin, L.V. (2006): Ranking procedures by pairwise comparison using random sets and the imprecise Dirichlet model, Applied Mathematics and Computation. 183(1), 394-408. (A version similar to the published paper can be downloaded.)
[10]  Utkin, L.V. (2006): Cautious analysis of project risks by interval-valued initial data, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 14(6). (A version similar to the published paper can be downloaded.)
[11]  Utkin, L.V. (2006): Cautious reliability analysis of multi-state and continuum-state systems based on the imprecise Dirichlet model, International Journal of Reliability, Quality and Safety Engineering. 13(5), 433-453. (A version similar to the published paper can be downloaded.)
[12]  Utkin, L.V. (2006): A method for processing the unreliable expert judgments about parameters of probability distributions, European Journal of Operational Research. 175(1), 385-398. (A version similar to the published paper can be downloaded.)
[13]  Utkin, L.V. (2005): Extensions of belief functions and possibility distributions by using the imprecise Dirichlet model, Fuzzy sets and Systems. 154(3), 413-431. (A version similar to the paper can be downloaded.)
[14]  Utkin L.V. and Augustin Th. (2005) Decision making under incomplete data using the imprecise Dirichlet model, Proc. of the 4th Int. Symposium on Imprecise Probabilities and Their Applications, ISIPTA'05, July, 2005, Pittsburg, USA.
[15]  Utkin L.V. and Augustin Th. (2005) Powerful algorithms for decision making under partial prior information and general ambiguity attitudes, Proc. of the 4th Int. Symposium on Imprecise Probabilities and Their Applications, ISIPTA'05, July, 2005, Pittsburg, USA.
[16]  Utkin, L.V. (2004): Probabilities of judgments provided by unknown experts by using the imprecise Dirichlet model, Risk, Decision and Policy. 9(4), 391-400. (A version similar to the published paper can be downloaded.)
[17]  Utkin, L.V. (2004): Reliability models of m-out-of-n systems under incomplete information, Computers & Operations Research. 31(10), 1565-1767. (A version similar to the published paper can be downloaded.)
[18]  Utkin, L.V. (2004): A new efficient algorithm for computing the imprecise reliability of monotone systems, Reliability Engineering and System Safety. 86(3), 179-190. (A version similar to the published paper can be downloaded.)
[19]  Utkin, L.V. (2004): Interval reliability of typical systems with partially known probabilities, European Journal of Operational Research. 153(3), 790-802. (A version similar to the published paper can be downloaded.)
[20]  Utkin, L.V. (2004): An uncertainty model of the stress-strength reliability with imprecise parameters of probability distributions. Zeitschrift für Angewandte Mathematik und Mechanik (Applied Mathematics and Mechanics). 84(10-11), 688-699. (A version similar to the published paper can be downloaded.)
[21]  Kozine, I.O. and Utkin, L.V. (2003): Variety of judgements admitted in imprecise statistical reasoning, Risk, Decision and Policy. 8, 111-120. (A version similar to the published paper can be downloaded.)
[22]  Utkin, L.V. (2003): A second-order uncertainty model for the calculation of the interval system reliability, Reliability Engineering and System Safety. 79(3), 341-351.
[23]  Utkin, L.V. (2003): Imprecise second-order hierarchical uncertainty model, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 11(3), 301-317.
[24]  Utkin, L.V. (2003): Imprecise reliability of cold standby systems, International Journal of Quality and Reliability Management. 20(6), 722-739. (A version similar to the published paper can be downloaded.)
[25]  Utkin, L.V. and Augustin, Th. (2003): Decision making with imprecise second-order probabilities. The 3-rd International Symposium on Imprecise Probabilities and Their Applications, July, Lugano, Switzerland, Carleton Scientific, pp. 545-559.
[26]  Utkin, L.V. (2003): A second-order uncertainty model of independent random variables: An example of the stress-strength reliability. The 3-rd International Symposium on Imprecise Probabilities and Their Applications, July, Lugano, Switzerland, Carleton Scientific, pp. 530-544.
[27]  Utkin, L.V. and Kozine, I.O. (2002): Stress-strength reliability models under incomplete information, International Journal of General Systems.31(6), 549-568. (A version similar to the published paper can be downloaded.)
[28]  Utkin, L.V. and Gurov, S.V. (2002): Imprecise reliability for some new lifetime distribution classes, Int. Journal of Statistical Planning and Inference. 105(1), 215-232. (A version similar to the published paper can be downloaded.)
[29]  Utkin, L.V. and Gurov, S.V. (2001): New reliability models based on imprecise probabilities. Chapter 6. Edited book: Advanced Signal Processing Technology by Soft Computing. World Scientific, 110-139.
[30]  Utkin, L.V. and Shubinsky, I.B. (2000): Unconventional Methods of the Information System Reliability Assessment. Saint Petersburg. Lubavich Publ. 173 pp. (in Russian)
[31]  Utkin, V.S. and Utkin, L.V.(2000): Reliability Analysis of Structural Units. School-book. 2ndEdition. Vologda. VoGTU, 166 pp.(in Russian)
[32]  Gurov, S.V., Utkin, L.V.and Shubinsky, I.B. (2000): Timing analysis of a fault-tolerant technique subject to hardware failures. Int. Journal of Reliability, Quality and Safety Engineering, 7(3), 153-165.
[33]  Gurov, S.V. and Utkin, L.V.(1999): Reliability of Systems under Incomplete Information. Saint Petersburg. Lubavich Publ. 160 pp. (in Russian)
[34]  Utkin, L.V. and Gurov, S.V. (1999): Imprecise reliability of general structures. Knowledge and Information Systems. 1, 459-480. (A version similar to the published paper can be downloaded.)
[35]  Utkin, L.V. and Gurov, S.V. (1998): Steady-state reliability of repairable systems by combined probability and possibility assumptions. Fuzzy Sets and Systems. 97, 193-202.