Dr. Andrej Savic
Neurotechnology Consultant · Brain-Computer Interfaces · AI for Neural Data · Clinical Neurotechnology
Bringing neurotechnology
to life.
Across research, healthcare, and industry.
Helping companies, research teams, and clinics design, build, and clinically validate brain-computer interface systems and AI-powered neurotechnology solutions.
16+ Years in Neurotechnology
Years in Neurotechnology
100+ Scientific Publications
Scientific Publications
20+ Institutions Collaborated
Institutions Collaborated
Top 12 BCI Award 2024 Nominee (worldwide)
BCI Award 2024 Nominee (worldwide)
Expertise Where It Matters
Neurotech Companies
Building a product that reads, processes, or responds to brain signals? Getting the signal processing right, the algorithms validated, and the clinical evidence structured, so the technology actually works on real users, not just in the lab.
Research Teams & Institutions
Deep EEG/BCI expertise for projects that don't have it in-house. From experimental design and signal acquisition to data analysis and publication-ready results.
Clinics & Rehabilitation Centers
Integrating novel methods such as brain-computer interfaces, neurostimulation, and machine learning protocols into clinical practice. Bridging the gap between state-of-the-art science and clinical workflow, for neurorehabilitation, outcome assessment, and biomarker implementation.
Investors & Decision Makers
Independent technical due diligence for neurotech investments and technology acquisitions. Assessing feasibility, scientific validity, and competitive positioning.
BCI Award 2024 Nominee
Selected among the top 12 projects worldwide (from 80+ candidates) for a novel brain-computer interface system for somatosensory rehabilitation after stroke: a completely new approach to sensory recovery using electrotactile stimulation controlled by brain signals.
Dr. Andrej Savic is a full research professor and Associate Editor of IEEE Transactions on Neural Systems and Rehabilitation Engineering, the leading journal in the field. He builds AI-powered brain-computer interface systems and takes them all the way to clinical validation with real patients. His work spans BCI design, EEG signal processing, machine learning for neural data, and clinical neurotechnology for stroke, ALS, Parkinson's disease, multiple sclerosis, dyslexia, and pain. He has led funded research projects, supervised PhD students, and collaborated with research groups globally.