INVITED SPEAKERS

 

Prof. Jeroen Bergmann
University of Southern Denmark, Denmark

 

Jeroens' research focuses on developing innovative technologies for healthcare and the processes needed to do so. He is the Head of Department of Technology and Innovation at SDU and fellow at the University of Oxford. Jeroen studied at London, Amsterdam, as well as Oxford, and holds or has held (visiting) teaching and/or research positions at some of the top institutions including King's College London, Imperial College London, University of Oxford, MIT and Harvard. He is co-founder of the RegTech platform RegMetrics which guides users through the European regulations for medical devices and he is inventor of the pelvic floor training device that has allowed Elvie to become a leading global FemTech company. Throughout his tenure at Oxford, Jeroen has authored numerous publications, shedding light on the intricate challenges and opportunities within the field of medical device design, validation, and regulatory compliance. His multidisciplinary approach merges engineering principles with business and medical knowledge, contributing to the creation of cutting-edge solutions that address under-served healthcare needs.

 

 

Assoc. Prof. Zhen Cao
Zhejiang University, China

 

Dr. Zhen Cao received his B.S. degree in Microelectronics from Fudan University, Shanghai, China in 2010. He obtained his Ph.D in Electronic and Computer Engineering from the Hong Kong University of Science and Technology (HKUST) in 2014 and was a postdoctoral fellow in the same group at HKUST from 2014 to 2015. From 2015 to 2016, he worked as a postdoctoral fellow in the Department of Electrical Engineering at Princeton University. He is now an Associate Professor in College of Information Science and Electronic Engineering of Zhejiang University. He has led many national projects including the National Key R&D Program and the National Natural Science Foundation. He has published over 60 papers in international peer-reviewed journals such as Nature Communications, ACS Nano, Small, Analytical Chemistry, and presented many invited talks at the international conferences and symposia including Transducer, Microtas, IEDM. His research interests primarily include silicon-based micro/nanofabrication, biomicrofluid

 

 

Asst. Prof. Juliana A. Knocikova
University of Ostrava, Czech Republic

 

Juliana A. Knocikova, Ph.D. is a researcher and university lecturer specializing in biomedical engineering, biophysics, and neuroscience. She currently serves as an assistant professor and research scientist at the Department of Cybernetics and Biomedical Engineering at VSB – Technical University of Ostrava, and at the Institute of Laboratory Medicine, Faculty of Medicine, University of Ostrava, Czech Republic. Her work focuses on mathematical modeling in biomedicine and neuroscience, biosignal recording and analysis, and academic teaching. Previously, she developed the Biocybernetics of Physiological Processes research group at the University of Chemistry and Technology in Prague. She has held research positions at Charles University, the National Institute of Mental Health, and several international institutions in France, Austria, and Slovakia. Her research interests include neurophysiology, quantitative biomarkers in neuropsychiatric disorders, and IT infrastructure for biomedical data. She holds degrees

 

Speech Title: "Exploring Brain Complexity Through EEG: A Technological Leap in Modern Psychiatry"

 

Speech Title: Neurophysiological data pose complex challenges for medical analysis due to their nonlinear, irregular, and non-stationary nature. Traditional techniques, such as power spectral analysis, are not sufficiently equipped to capture the dynamic intricacies of brain signals, particularly in psychiatric and psychological contexts. n mental health research, especially in psychiatry and psychology, advanced signal processing tools have become essential. Technologies such as wavelet analysis, chaos theory, and nonlinear dynamics, including entropy and fractal dimension, enable deeper insight into the fluctuating activity of the brain. Among these, approximate entropy stands out because it quantifies the unpredictability and regularity of biosignals, serving as a potent marker of cognitive and emotional processing. lectroencephalography (EEG), widely used in clinical and research settings, is increasingly recognised as a valuable source of neurophysiological data. However, its full diagnostic potential, particularly f