Dr Evgeny Mirkes

Research Associate

Profile

Evgeny Mirkes (Ph.D. Sc.D.) is a Research Associate at the University of Leicester and a leader of several projects in the Data Mining. His main research interests are biomathematics data mining and software engineering neural network and artificial intelligence. He has led and supervised many projects in data analysis and the development of decision-support systems for computational diagnosis and treatment planning and has participated in applied projects in Natural Language Processing in the area of social media data analysis. He has rich experience in Predictive Mathematical and Computational Modelling and in finding solutions to classification clustering and auto coding problems. In particular he developed a special programming language for Neural Networks created a theory on geometrical complexity which is applicable to approximators of several types and allows the comparing of various methods of data approximations. He developed a system for online diagnosis of lymphoma in veterinary application (for Avacta Animal Health) one system for analysis of geophysical borehole information (for Weatherford) and has led many other projects of this type.

Research

Main area of interest are:

  • Artificial Intelligence
  • Applied statistics
  • Machine learning
  • Data mining
  • Natural language processing

Dr Mirkes elaborated a new and universal framework to minimise arbitrary sub-quadratic error potentials in machine learning and developed new machine learning methods which achieve orders of magnitude with faster computational performance than corresponding state-of-the-art methods.

The new powerful version of Supervised PCA was developed. This version allow significantly reduce dimension of space used to solve specific classification problem.

Several projects was performed with College of Life Science: with TARN in collaboration with Professor Timothy Coats and Dr Damian Roland and with Professor Thomas Yates, Dr Alex Rowlands and Dr Petra Jones.

Several collaborative project with Professor Stanislav S. Piletsky from chemistry department. There were several successful industrial projects with Weatherford Ltd. Bellrock Group SPRINT and other.

Publications

Fehrman, E., Egan, V., Gorban, A.N., Levesley, J., Mirkes, E.M. and Muhammad, A.K., 2019. Personality Traits and Drug Consumption: A story told by data. Springer.

Manso, A.S., Chai, M.H., Atack, J.M., Furi, L., Croix, M.D.S., Haigh, R., Trappetti, C., Ogunniyi, A.D., Shewell, L.K., Boitano, M. and Clark, T.A., 2014. A random six-phase switch regulates pneumococcal virulence via global epigenetic changes. Nature communications, 5(1), pp.1-9.

Mirkes, E.M., Coats, T.J., Levesley, J. and Gorban, A.N., 2016. Handling missing data in large healthcare dataset: A case study of unknown trauma outcomes. Computers in biology and medicine, 75, pp.203-216.

Gorban, A.N., Mirkes, E.M. and Zinovyev, A., 2018, July. Data analysis with arbitrary error measures approximated by piece-wise quadratic PQSQ functions. In 2018 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.

Rowlands, A.V., Mirkes, E.M., Yates, T., Clemes, S., Davies, M., Khunti, K. and Edwardson, C.L., 2017. Accelerometer-assessed physical activity in epidemiology: are monitors equivalent?

Supervision

  • I currently supervise 2 PhD students as the first supervisor.
  • I am the second supervisor of one PhD student and the second supervisor of two more very resent PhD students.
  • 1 industrial MPhil student has been supervised to completion.
  • 3 PhD students have been supervised to completion as the second supervisor.
  • Several MSc projects supervised each year.

Teaching

  • 2021 MA3080/MA4080/MA7080 Mathematical Modelling - module convenor.
  • 2019, 2022 MA3022/MA4022/MA7022 Data Mining and Neural Network - module convenor.
  • 2013-2020 MA3080/MA4080/MA7080 Mathematical Modelling - Teaching assistant.
  • 2013-2021 MA3022/MA4022/MA7022 Data Mining and Neural Network  - Teaching assistant.

Conferences

  • IJCNN-2020 JETC-2021

Media enquiries

Get in touch for media enquiries, expert opinion, interviews, images or video.

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