Alexander Backa

VC 3.16

+421 41 513 7610

alexander.backa@uniza.sk


Ing. Alexander Backa, PhD., is a postdoctoral researcher at the UNIZA Research Centre. His work focuses on combustion in small-scale heat sources, with an emphasis on experimental measurements, numerical simulations, and advanced data processing. His research primarily addresses biomass combustion, operational performance assessment of small combustion appliances, analysis of gaseous emissions and particulate matter (PM) formation, and the design of emission-reduction measures, including applications of electrostatic precipitation and automated control and regulation of combustion systems. His expertise integrates CFD simulations (ANSYS Fluent), energy balance calculations, and predictive modelling in MATLAB with experimental validation. He also targets the application of AI/ML methods for processing emission data and for predicting and controlling combustion behaviour.
In his publication activity, he focuses on topics such as combustion of various solid fuels, spatial distributions of temperature, emissions, and PM within the combustion zone, combustion optimisation through automated control, and improving separation efficiency. He is the author/co-author of more than 30 publications (journal articles, conference proceedings, etc.). To date, his citation record includes 32 citations in Web of Science and 28 citations in Scopus, with an H-index of 3.
A substantial part of his professional development has been shaped by international mobility and collaboration, including Erasmus+ research stays in Poland and Italy (LEAP s.c.a r.l., Piacenza; Silesian University of Technology, Gliwice; University of Agriculture in Krakow) and active participation in international conferences, where he presented research on combustion, flue-gas flow, and data-driven emission modelling. In teaching, during his PhD studies he led laboratory classes in Fluid Mechanics and Thermodynamics.



  • Seal of Excellence award (HORIZON-MSCA-2025-PF-01-01) for the project “Innovative Methods of Particulate Matter Reduction by Optimization of Gas Duct Geometry”.
  • Best paper award at the international EAI conference (for a paper on ML regression in MATLAB for predicting gaseous emissions during pellet combustion).


  • UNIZA Grant Scheme No. 21016. Use of image data and machine learning for emission prediction and classification of combustion phases in fireplace stoves for air-supply control systems. - University grant for early-career researchers under 35, 2025–2026 – Principal Investigator.
  • UNIZA Grant Scheme No. 15900. Mitigation of issues in combustion of fuels with low ash fusion temperatures using predictive models, with a focus on phytomass combustion. - University grant for PhD candidates, 2021–2022 – Principal Investigator.