Resume
Academic Achievements
- 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.
Miscellany
- No personal interests mentioned.