Volodymyr Turchenko


Phone: (403) 394-3973
e-mail: vtu@uleth.ca
Lab: EP 1241A

Position

Postdoctoral Fellow

Supervision

Dr. Artur Luczak, Dr. Aaron Gruber and Dr. Robert Sutherland

Research Interests

I am interested in the application of artificial neural networks, in particular unsupervised and deep learning techniques, to study information processing in genetic and neuronal systems by the analysis of electrophysiological, genetic and/or epigenetic data collected from animals. Recent deep learning architectures have been successfully applied to fields of computer vision, automatic speech recognition, natural language processing, audio signal recognition and other fields. Deep learning algorithms are capable of representing high-level abstractions or features from complex data sets and pick out which features are useful for solving specific tasks. My research lies at the interface of machine learning and neuroscience, with the aim of breakthroughs in understanding brain function.

Degrees

  • Ph.D., Lviv Polytechnic National University, Ukraine (2001).
  • Dipl. Eng. (honors), Brest Polytechnic Institute, Belarus (1995).

Biography

Volodymyr Turchenko received his Engineer Diploma (equiv. M.Sc.) with honours in System Engineering from Brest Polytechnic Institute, Belarus in 1995 and his Ph.D. degree in Computer Engineering from Lviv Polytechnic National University, Ukraine in 2001. He was promoted to an Associate Professor rank at the Information Computing System and Control Department at the Ternopil National Economic University (TNEU), Ukraine in 2004. He worked as an Assistant and Associate Professor at the Research Institute for Intelligent Computer Systems and Information Computing System and Control Department at TNEU, Ukraine in 2000-2009, 2011-2012 and 2013-2014. Working at TNEU he was a recipient of INTAS YSF Postdoctoral Fellowship grant during 2004-2006. He worked in the Supercomputing Center for Engineering Computations at the University of Calabria, Italy as a Postdoctoral Fellow funded by the FP7 Marie Curie IIF Postdoctoral Fellowship programme in 2009-2011. He was a Fulbright Scholar in Innovative Computing Lab at the University of Tennessee, USA in 2012-2013. In January 2015 Dr. Turchenko joined Polaris Group at the Canadian Centre for Behavioural Neuroscience at the University of Lethbridge as a Postdoctoral Fellow.

Read more about Volodymyr Turchenko here.

Recent Publications

  1. Turchenko V, Chalmers E, Luczak A. Deep Convolutional Auto-Encoder with Pooling – Unpooling Layers in Caffe. arXiv preprint (2017) Paper, Code.
  2. Turchenko V, Luczak A. Creation of a Deep Convolutional Auto-Encoder in Caffe. arXiv preprint (2015) Paper, Code.
  3. Golovko V., Kroshchanka A., Turchenko V., Jankowski S., Treadwell D., A New Technique for Restricted Boltzmann Machine Learning, 8th IEEE Intern. Conf. on Intelligent Data Acquisition and Advanced Computing Systems IDAACS’15, Warsaw, Poland, 182-186 (2015).
  4. Turchenko V. Parallel batch pattern training algorithm for MLP with two hidden layers on many-core system, Advances in Intelligent Systems and Computing, 290, 537-544 (2014).
  5. Turchenko V., Golovko V. Parallel batch pattern training algorithm for deep neural network, Intern. Conf. on High Performance Computing & Simulation HPCS’14, Bologna, Italy, 697-702 (2014).
  6. Turchenko V., Bosilca G., Bouteiller A., Dongarra J. Efficient parallelization of batch pattern training algorithm on many-core and cluster architectures, 7th IEEE Intern. Conf. on Intelligent Data Acquisition and Advanced Computing Systems IDAACS’13, Berlin, Germany, 692-698 (2013).
  7. Turchenko V., Golovko V., Sachenko A. Parallel batch pattern training of recirculation neural network, 9th Intern. Conf. on Informatics in Control, Automation and Robotics ICINCO’12, Rome, Italy, 644-650 (2012).
  8. Turchenko V., Golovko V., Sachenko A. Parallel training algorithm for RBF neural network, 7th Intern. Conf. on Neural Networks and Artificial Intelligence ICNNAI’12, Minsk, Belarus, 47-51 (2012).
  9. Paliy I., Lamonaca F., Turchenko V., Grimaldi D., Sachenko A. Detection of micro nucleus in human lymphocytes altered by Gaussian noise using convolution neural network, IEEE Intern. Instrumentation and Measurement Technology Conf. I2MTC’11, Binjiang, Hangzhou, China, pp. 1097-1102 (2011).
  10. Turchenko V., Grandinetti L. Application of BSP-based computational cost model to predict parallelization efficiency of MLP training algorithm, LNCS, 6354, 327-332 (2010).
  11. Paliy I., Lamonaca F., Turchenko V., Grimaldi D., Sachenko A. Micro nucleus detection in human lymphocytes using convolutional neural network, LNCS, 6352, 521-530 (2010).
  12. Turchenko V., Grandinetti L. Scalability of enhanced parallel batch pattern BP training algorithm on general-purpose supercomputers, Advances in Intelligent and Soft-Computing, 79, 518-526 (2010).
  13. Turchenko V., Grandinetti L., Bosilca G., Dongarra J. Improvement of parallelization efficiency of batch pattern BP training algorithm using OpenMPI, Procedia Computer Science, 1 (1), 525-533 (2010).
  14. Turchenko V., Grandinetti L. Parallel batch pattern BP training algorithm of recurrent neural network, 14th IEEE Intern. Conf. on Intelligent Engineering Systems INES’10, Las Palmas of Gran Canaria, Spain, 25-30 (2010).