YOUR BROWSER IS OUT-OF-DATE.

We have detected that you are using an outdated browser. Our service may not work properly for you. We recommend upgrading or switching to another browser.

Sign in

 

Faculty of Electronics

Prof. Olgierd Unold, DSc, PhD, Eng

Email: olgierd.unold@pwr.edu.pl

Unit: Faculty of Information and Communication Technology (N) » Department of Computer Engineering

Olgierd Unoldul. Z. Janiszewskiego 11/17, 50-372 Wrocław
building C-3, room 324
phone +48 71 320 2279

Office hours

  • Tuesday 11.00-13.00
  • Thursday 11.00-13.00

Research fields

  • Machine learning (grammatical inference); computational intelligence (evolutionary algorithms, learning classifier systems, fuzzy rule systems); bioinformatics; DNA Computing; natural language processing.

Recent papers

2017

  • Ptak R., Żygadło B., Unold O., Projection-based text line segmentation with a variable threshold. International Journal of Applied Mathematics and Computer Science. 2017, vol. 27, nr 1, 195-206.

2016

  • Unold O., Tarnawski R., Cultural Ant Colony Optimization on GPUs for Travelling Salesman Problem. In: Pardalos P., Conca P., Giuffrida G., Nicosia G. (eds) Machine Learning, Optimization and Big Data. MOD 2016. Lecture Notes in Computer Science. 2016, vol. 10122. Springer, Cham, 317-329.
  • Wieczorek W., Unold O., Use of a novel grammatical inference approach in classification of amyloidogenic hexapeptides. Computational and Mathematical Methods in Medicine. 2016, vol. 2016,1-8.

2015

  • Unold O., Tagowski T., A Parallel Consensus Clustering Algorithm. In: Pardalos P., Pavone M., Farinella G., Cutello V. (eds) Machine Learning, Optimization, and Big Data. Lecture Notes in Computer Science. 2015, vol. 9432. Springer, Cham, 318-324.

2014

  • Walkowicz E., Unold O., Maciejewski H., Skrobanek P., The effect of selected factors on the length of gestation period in Silesian mares. Animal Science Papers and Reports. 2014, vol. 32, nr 1, 55-64.

2013

  • Stanisławski J., Kotulska M., Unold O., Machine learning methods are compatible with 3D profile classification of amylogenic hexapeptides, BMC Bioinformatics. 2013, vol. 14 (21), 1-19.
  • Kotulska M., Unold O., On the amyloid datasets used for training PAFIG - how (not) to extend the experimental dataset of hexapeptides. BMC Bioinformatics. 2013, vol. 14, [art.] 351, 1-8.

Papers in DONA database

Politechnika Wrocławska © 2024