Abstract:

Analyzing non-stationary signals remains a key challenge across many areas of science and engineering, from biomedical measurements to environmental and mechanical systems. Traditional Fourier-based methods often fail to capture transient or evolving patterns that carry critical information. In this talk, I will introduce time-frequency distributions as a versatile framework for examining complex, dynamic signals. I will also discuss compressive sensing, an advanced technique that enables accurate reconstruction of signals from limited measurements, improving efficiency in data acquisition and analysis. When combined with machine learning methods, these approaches offer powerful tools for feature extraction, pattern recognition, and interpretation across diverse signal types. Through case studies including EEG recordings and tire sensor data as representative real-world examples, I will illustrate how these techniques address practical challenges in signal analysis.

Biography:

Vedran Jurdana received his Ph.D. in Electrical Engineering from the Faculty of Engineering, University of Rijeka, Croatia, in 2023. He is a Postdoctoral Researcher at the Department of Automation and Electronics, University of Rijeka, where he leads the Laboratory for Electronics. His research focuses on EEG signal processing, machine learning, compressive sensing, eye-tracking, and assistive technologies, with an emphasis on data-driven approaches for biomedical signal analysis. He has led and contributed to multiple scientific research projects funded by the Croatian Science Foundation and the University of Rijeka. Dr. Jurdana has established international research collaborations through visits to Graz University of Technology and Johannes Kepler University Linz (Austria), ELTE University in Budapest (Hungary), and Tampere University (Finland). He has served as a member of the Technical Program Committees of international conferences, including CoBCom 2024 and ATAAC 2026. He delivered an invited talk at the ASPAI 2025 conference and has presented his research at international institutions during his research visits. In recognition of his scientific contributions, he received the University of Rijeka Foundation Award for 2024 in the category of Young Scientist in Technical and Biotechnical Sciences. He has been actively involved in higher education teaching since 2017 and has authored numerous scientific publications in signal processing and biomedical engineering.