Dr. Marzena Miesikowska | Automation Robotics Award | Best Researcher Award

Dr. Marzena Miesikowska | Automation Robotics Award | Best Researcher Award

Dr. Marzena Miesikowska, Kielce University of Technology, Poland 

Marzena Mięsikowska is an Assistant Professor at Kielce University of Technology in Poland. She holds a PhD in Automation and Robotics and a Master’s degree in Computer Science, both from Kielce University of Technology. Her research interests encompass automation, robotics, information systems, and the analysis of acoustic and speech signals, particularly for drone applications and patient rehabilitation. She has completed a National Science Centre project and participated in the “Future Technologies for Defense” project by the National Centre for Research and Development. Mięsikowska has published multiple books and book chapters and holds a patent for a voice quality assessment method. She is also involved in editorial work and various academic collaborations.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award: Marzena Mięsikowska

Dr. Marzena Mięsikowska is an Assistant Professor at Kielce University of Technology with a robust background in automation and robotics, information systems, and acoustic signal analysis. Her diverse expertise spans drone acoustic signal analysis, speech signal processing, and metrology.

Education:

  • Ph.D. in Automation and Robotics
    Kielce University of Technology, Kielce, Poland
  • Master of Computer Science
    Kielce University of Technology, Kielce, Poland

Work Experience:

  • Assistant Professor
    Kielce University of Technology, Kielce, Poland
    Current Position
  • Metrologist
    Central Office of Measures, Warsaw, Poland
    Past Position

Publication top Notes:

Analysis of Polish Vowels of Tracheoesophageal Speakers

Discriminant analysis of voice commands in a car cabin | Analiza dyskryminacyjna komend głosowych w kabinie pojazdu

Analysis of Sound Levels and Speech Intelligibility in the Presence of X4 Unmanned Aerial Vehicle in External Environmental Conditions

Discriminant analysis of voice commands in the presence of an unmanned aerial vehicle

Speech intelligibility in the presence of X4 unmanned aerial vehicle