Key research themes
1. How do real-time feedback-driven methods optimize precision and speed in single-particle tracking?
This research theme investigates different real-time feedback-driven single-particle tracking (RT-FD-SPT) techniques, focusing on their comparative performance in terms of localization precision, tracking speed, and ability to handle diffusion dynamics. It matters because RT-FD-SPT enables in vivo single-molecule spectroscopy (SMS) by tracking freely diffusing biomolecules with high spatiotemporal resolution, overcoming limitations of conventional image-based tracking.
2. What advances enable robust and computationally efficient multi-target tracking with particle filtering?
This research area explores novel algorithmic and computational strategies leveraging particle filtering (PF) and related probabilistic frameworks to track multiple targets in complex scenarios involving occlusions, high target density, dynamic environments, and changing target appearance. Effective multi-target tracking is crucial for applications in surveillance, traffic monitoring, and biomedical imaging where targets interact or cross each other.
3. How can particle tracking methods be enhanced for complex flow environments and 3D tracking applications?
This theme concentrates on methodological advancements in particle tracking applied to fluid flows and 3D imaging contexts. It covers experimental setups, novel algorithms for particle motion reconstruction, and application of particle filters in environments with complex flow dynamics like Couette flows or turbulent convection. The focus is on improving trajectory reconstruction accuracy, measurement resolution, and computational efficiency to better understand fluid mechanics and support applications in experimental fluid dynamics and robotics.



























































