AI Multi-modal Sensing
The AIMS lab researches and develops AI models for systems equipped with sensors of multiple different modalities. We foster expertise in AI analysis of RGB, thermal, depth, LiDAR, acoustic, sonar and radar sensor data. When the multi-modal sensors are combined in a sensor suite, they often provide capabilities similar to the human 鈥�5-sense system鈥�, which bring the desired full situational awareness. This awareness is vital in our industrial partners in public safety & security, smart cities, defense, critical infrastructure inspection and intelligent transportation.
Research Profile
We conduct our research in close collaboration with the Departments of Mechanical Engineering, Mathematics & Computer Science and Industrial Engineering & Industrial Sciences at 黑料福利网. Externally, we work together with research institutions such as Reality Labs at Meta, MARIN, Inria, TNO, SIRRIS, as well as with the Universities of Munich, Delft, Maastricht, Liege, Birmingham and Gent.
Research Profile
The AIMS lab specializes in advanced artificial intelligence methods for multi-modal sensor systems, enabling machines to perceive and interpret complex environments in real-time through the fusion of heterogeneous data sources. The core objective of the lab is to advance the real-time fusion and interpretation of multi-modal data through cutting-edge AI techniques. The research focuses on few-shot, unsupervised and self-supervised learning, casual reasoning, 4D gaussian splatting, embodied AI, and efficient edge deployment. By integrating these approaches, the lab develops methods capable of detecting events across modalities, localizing threats and objects in 3D space, and identifying abnormal patterns without requiring extensive labeled datasets.
Lees meerMeet some of our Researchers
Recent Publications
Our most recent peer reviewed publications