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  3. Konstantin Semenov
Konstantin Semenov
Konstantin Semenov

Ph.D.

Associate Professor - Higher School of Computer Technology and Information Systems Peter the Great St. Petersburg Polytechnic University

English proficiency:

Fluent

Research projects:

Russian Science Foundation
2025-2026. Head of grant 25-21-20109 «Improving tools for studying processes affecting the in vitro transcription reaction in pilot production of RNA vaccines».
2025-2026. Participant in grant 25-29-20141 «Optimal and suboptimal methods for reconciling and refining inaccurate industrial data based on co-opting information about their internal relationships and about mathematical models of digital production»

Research topics:

  1. Methods of spectral decomposition of measured signals, consistent with their accuracy.
  2. Coordination of the architecture and complexity of neural networks for processing measured signals with the accuracy of the information being processed.
  3. Methods and means of extrapolating measured signals, consistent with the accuracy of the information being processed.
  4. Methods and means of restoring gaps in measured signals, consistent with the accuracy of the information being processed.
  5. Methods and means of testing statistical hypotheses based on interval data.
  6. Methods for assessing the approximations accuracy of replacing software systems based on floating-point computations by fixed- point calculation systems.
  7. Methods and means for rapid estimating of robust analogues for random variables moments based on the median operator. 8)Methods and means for constructing reliable confidence intervals based on small samples.
  8. Optimal methods and means for estimating the global sensitivity of programs to variations in input arguments.
  9. Robust measures of skewness and kurtosis of unimodal probability distributions.
  10. Localization of faults in electric power systems based on the results of control measurements.

Field of study:

Applied Mathematics, Instruments

Research interest:

Probability theory and mathematical statistics, data processing, processing of inaccurate and incomplete data, decision-making under conditions of uncertainty, measurement methods, instrumentation, information-measuring and control systems, metrologically significant software, metrology, mathematical modelling, algorithmization, numerical methods, computational mathematics, physical modelling of processes in fluids, applied hydrodynamics, interaction of sea waves with hydraulic structures, performing meta-analyses, the impact of eco-innovations on the financial performance of companies (in the context of their size), scientometrics.

Research highlight:

Most significant results of intellectual activity over the past 5 years.

  1. Taraskin A.S., Semenov K.K., Lozhkov A.A., Vasin A.V., Klotchenko S.A., Zabrodskaya Ya.A. A method for quantitative multiplex analysis of alpha-2-macroglobulin, fetuin A and serum amyloid a1 as inflammatory factors in blood serum using MALDI- TOF mass spectrometry. Patent for invention 2789503 C1, 03.02.2023. Application No. 2022112637 dated 11.05.2022.
  2. Garanin V .A., Semenov K.K. Program for nonparametric reconciling the results of joint measurements of interrelated quantities using the method of probability density function’s projection restoration / Certificate of registration of computer program 2023610445, 11.01.2023. Application No. 2022686089 dated 27.12.2022.
  3. Garanin V.A., Semenov K.K. Program for assessing the increase in measurement accuracy due to considering the known functional relationships between measured quantities / Certificate of registration of computer program 2023610961, 16.01.2023. Application No. 2022686101 dated 27.12.2022.
  4. Tselischeva A.A., Semenov K.K., Garanin V.A. Program for calculating approximate error estimates for solutions of systems of nonlinear equations with imprecise parameters based on local polynomial approximation / Certificate of computer program registration 2023617702, 12.04.2023. Application No. 2023615916 dated 30.03.2023.

Specific requirement:

  • To be sufficiently trained in the field of probability theory and mathematical statistics, computational mathematics – for Ph.D. theses in the field of data processing.
  • To be sufficiently trained in engineering – for Ph.D. theses in the field of instrumentation.
  • To have experience in preparing and publishing scientific articles in leading international scientific journals or conferences.
  • Skills of software development (preferred – Python and/or Matlab, R).

Main publications:

  1. Belyaev, N.D., Lebedev, V.V., Nudner, I.S., Mishina, A.V., Semenov, K.K., Shchemelinin, D.I. (2014) Experimental study of tsunami-type waves impact on soil at foundations of offshore gravity platforms. Magazine of Civil Engineering. Vol. 50(6). P. 4-121. DOI: 10.5862/MCE.50.1 [Q2]
  2. Lebedev, V.V., Nudner, I.S., Belyaev, N.D., Semenov, K.K., Schemelinin, D.I. (2018) The formation of the seabed surface relief near the gravitational object. Magazine of Civil Engineering.Vol. 79(3). P. 120-131. DOI: 10.18720/MCE.79.13 [Q1]
  3. Semenov, K.K., Reznik, L.K., Solopchenko, G.N. (2015) Fuzzy intervals application for software metrological certification in measurement and information systems. International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems. Vol. 23. P. 95-104. DOI: 10.1142/S0218488515400085. [Q2]
  4. Taraskin, A.S., Semenov, K.K., Protasov, A.V., Lozhkov, A.A., Tyulin, A.A., Shaldzhyan, A.A., Ramsay, E.S., Mirgorodskaya, O.A., Klotchenko, S.A., Zabrodskaya, Y.A. (2021) Quench me if you can: Alpha-2-macroglobulin trypsin complexes enable serum biomarker analysis by MALDI mass spectrometry. Biochimie. Vol. 185. P. 87-95. DOI: 10.1016/j.biochi.2021.03.005. [Q1]
  5. Taraskin, A.S., Semenov, K.K., Lozhkov, A.A., Baranovskaya, I.L., Protasov, A.V., Ramsay, E.S., Tyulin, A.A., Mirgorodskaya, O.A., Vasin, A.V., Klotchenko, S.A., Zabrodskaya, Y.A. (2022) A novel method for multiplex protein biomarker analysis of human serum using quantitative MALDI mass spectrometry. Journal of Pharmaceutical and Biomedical Analysis. Vol. 210. Paper 114575. DOI: 10.1016/j.jpba.2021.114575. [Q1]
  6. Semenov K.K., Taraskin A.S., Yurchenko A., Baranovskaya I., Purvinsh L., Gyulikhandanova N., Vasin A.V. (2023). Uncertainty estimation for quantitative agarose gel electrophoresis of nucleic acids. Sensors. Vol. 23. No. 4. Paper 1999. DOI: 10.3390/s23041999 [Q1]
  7. Semenova A.S., Semenov K.K., Strochevoy M.A. (2023). One, Two, Three: How Many Green Patents Start Bringing Financial Benefits for Small, Medium and Large Firms? Economies. Vol. 11(5). Paper 137. DOI: 10.3390/economies11050137 [Q2]
  8. Semenova A.S., Semenov K.K., Storchevoy M.A. (2024) Green patents or growth? European and the USA firms' size dynamics and environmental innovations financial gains. Sustainability. Vol. 16(15). Paper 6438. DOI: 10.3390/su16156438 [Q1]
  9. Semenova A.S., Semenov K.K. (2024) Does green mean paying? Environmental innovations and financial performance: meta-analytical insights/approach. Journal of Infrastructure, Policy and Development. Vol. 8(14). Paper 5255. DOI:24294/jipd5255 [Q2]
  10. Garanin V.A., Semenov K.K. (2024). Increasing measurement accuracy by nonparametric data reconciliation. Measurement. Vol. 238. Paper 115235. DOI: 10.1016/j.measurement.2024.115235 [Q1]