Supported by an NGF AiNed Fellowship Grant. Selected publications include 'Helmsman: Autonomous Synthesis of Federated Learning Systems via Multi-Agent Collaboration', 'Electrocardiogram–Language Model for Few-Shot Question Answering with Meta Learning', and 'Q-Heart: ECG Question Answering via Knowledge-Informed Multimodal LLMs'.
Research Experience
Currently an Assistant Professor (tenured) at Eindhoven University of Technology. Previously, he worked as a researcher at Google Brain and as an industrial fellow at the University of Cambridge’s Mobile Systems Lab. Before joining TU/e as faculty, he was a Research Scientist in AI at Philips Research, contributing to advancing AI for sensing applications.
Education
Ph.D. (cum laude) from Eindhoven University of Technology, Department of Mathematics and Computer Science, researching self-supervised learning for sensory data (ECG, EEG, IMU, PPG, and Audio). MSc. (cum laude) in Computer Science with a specialization in Data Science and Smart Services from the University of Twente.
Background
Research interests: Decentralized AI, Deep Learning, Self-Learning Systems. Specializes in Agentic AI, Multimodal Language Models, Self-Supervised Learning, Federated Learning, Audio Understanding, and their applications in Healthcare and High-tech Industries.