Evgeny Mirkes

Research associate, PhD, Dr.Sc.Evgeny M


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.

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.

Bibliography. The almost complete list of publications can be found in Google scholar

Opensource software repositories where I was developer or one of developer:

Elastic maps

The method of generalized regression regularization through PQSQ technique is presented. This approach includes lasso, elastic net and ridge regression as particular case.

Data imputation for visualisation

Classification supervised PCA

PQSQ regression

Library to save Java canvas as EPS file

Elastic principal graphs

Matlab and Java implementations of data analysis methods based on piece-wise quadratic approximation error (PQSQ)

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Contact details

Department of Mathematics
University of Leicester
University Road
Leicester LE1 7RH
United Kingdom

Tel.: +44 (0)116 229 7407

Campus Based Courses

Undergraduate: mathsug@le.ac.uk
Postgraduate Taught: mathspg@le.ac.uk

Postgraduate Research: pgrmaths@le.ac.uk

Distance Learning Course  

Actuarial Science:

DL Study

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