Industrial Automation

Biography

Miroslaw Swiercz received his MSc and PhD (1984) degrees in control engineering from Warsaw University of Technology, Warsaw, Poland, in 1977 and 1984, respectively. He also received DSc (habilitation) degree in biocybernetics and biomedical engineering in 2001 from the Institute of Biocybernetics and Biomedical Engineering of Polish Academy of Sciences, Warsaw, Poland. From 1981 he is with the Faculty of Electrical Engineering of Bialystok Technical University (BTU), Bialystok, Poland. In 1987-1988 he worked as a Senior Developer in Tessel AB (Free Form Desing AB) – the software development company in Stockholm, Sweden. In 1992-1993 he worked as a Research Fellow in Water Software Systems, Department of Electronic & Electrical Engineering, De Montfort University, Leicester, UK. He is currently a Professor in the Chair of Automatic Control and Electronics and Head of the Faculty of Electrical Engineering of Bialystok Technical University. He is an author and co-author of over 70 publications – book chapters, journal articles and conference papers. Professor M. Swiercz is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE). In 2006-2007 he served as a President of the Polish Chapter of the IEEE Signal Processing Society. He is also a member-founder of the Polish Society of Artificial Neural Networks, a member of the Association of Polish Electrical Engineers (SEP), the Polish Society of Theoretical and Applied Electrotechnics (PTETiS) and the Polish Society for Measurement, Automatic Control and Robotics (POLSPAR). He is also a member of the International Federation of Automatic Control (IFAC) Technical Committee on Biosystems and Bioprocesses in the term of office 2008-2011. He also the vice-Dean of the Faculty of Electrical Engineering at Bialystok University of Technology from 1999 to 2005 and the Dean of the Faculty from 2005 to 2012. He also serve in the IFAC Technical Committee on Biosystems and Bioprocesses in the next term of office, i.e. from 2012 to 2014.

Research Interest

Artificial intelligence–based techniques for modeling and monitoring of biomedical processes, fault diagnosis with the use of signal processing and artificial intelligence techniques, detection of structure and parameter changes in dynamic processes, medical data classification and application of artificial intelligence and signal processing in medical decision support systems