Jacqueline (Jacky) Behrendt

Jacky Behrendt is a Master’s student in Mathematics at Technische Universität Berlin and a member of the Konrad Zuse School ELIZA. She works as a Student Assistant at the Intelligent Biomedical Sensing (IBS) Lab at TU Berlin and BIFOLD, where she develops machine learning tools for biomedical image sensing. Her research focuses on blind source separation methods—particularly independent component analysis (ICA)—for functional near-infrared spectroscopy (fNIRS) data analysis.

She has contributed to Cedalion, a toolbox for fNIRS signal analysis and synthetic data generation, and co-authored an international study on variability in fNIRS analysis. Jacky also collaborates with researchers in Boston on applying ICA to neuroimaging data and is actively involved in advancing signal processing techniques for fNIRS applications.