Professor of Data Science
NORDAKADEMIE Elmshorn
Since 2023 I teach and research in artificial intelligence, machine learning, data science, statistics, math and software engineering. My work focuses on building strong methodological foundations, connecting theory with real-world practice, and integrating modern AI in a meaningful and responsible way.
(Senior) Research Scientist
Philips Research Hamburg
From 2015 to 2023 I worked on AI-driven solutions for MRI, CT and ultrasound imaging. My contributions supported clinical workflows and product development across several modalities. I collaborated with international research groups, developed deep-learning tooling, and contributed to agile program structures as Scrum Master and Release Train Engineer.
Research in ML & Neuroimaging
UKE • NIRx • Fraunhofer FIRST
Earlier in my career I worked in academic and applied research on EEG/MEG & NIRS data analysis, functional connectivity, neuroimaging, signal processing, and multimodal data integration. This work shaped my expertise in combining statistical methods, machine learning, and complex biomedical data analysis.
Academic Background
TU Berlin • TU Hamburg
I hold a doctoral degree (Dr. rer. nat., summa cum laude) in machine learning and signal processing from TU Berlin, supervised by Dr. Guido Nolte and Prof. Dr. Klaus-Robert Müller. My dissertation focused on multivariate EEG/MEG analysis and brain connectivity:
http://files.aewald.net/PhDThesis_ArneEwald.pdf
I studied Informatik-Ingenieurwesen (Dipl.-Ing.) and General Engineering Science (B.Sc.) at TU Hamburg.