معرفی
Dubravko Kicic is a Ph.D. Visitor (Faculty) at the Department of Neuroscience and Biomedical Engineering at Aalto University, specializing in advanced brain stimulation techniques and neuroengineering. His work primarily focuses on transcranial magnetic stimulation systems and their clinical applications.
Education:
- Doctoral degree in Engineering and Technology from Helsinki University of Technology (awarded October 20, 2009)
- Master's degree in Engineering and Technology from Helsinki University of Technology (awarded June 14, 2005)
Kicic's research centers on non-invasive brain stimulation technologies, particularly transcranial magnetic stimulation (TMS). His work spans neuroscience, biomedical engineering, and clinical applications for treating neurological and psychiatric conditions. He investigates how to optimize brain stimulation targeting, develop multi-locus TMS systems, and create robotic platforms for precise stimulation delivery. His fingerprint includes expertise in Transcranial Magnetic Stimulation, Behavioral Addiction, Magnetoencephalography, Neuromodulation, Pulse Rate analysis, and Signal Space engineering.
Recent publications demonstrate a clear trend toward developing more precise and effective brain stimulation systems. Kicic's work focuses on multi-locus TMS for simultaneous stimulation of multiple brain areas, robotic targeting systems for improved accuracy, and real-time identification of brain states to optimize stimulation timing. His research bridges engineering innovation with clinical neuroscience applications, particularly for depression and pain treatment.
Kicic has supervised at least one thesis and has been involved in media coverage regarding how magnetic brain stimulation can help patients with depression and pain. His collaborative work shows extensive international connections in the neuroscience and biomedical engineering fields.
His research contributes to UN Sustainable Development Goals related to good health and well-being through developing advanced neurotechnologies for clinical applications.
