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
I hold a doctoral degree (Dr. rer. nat., summa cum laude) in machine learning and signal processing from TU Berlin, supervised by Prof. 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.