Key research themes
1. How do real-time feedback algorithms improve spatiotemporal resolution and enable concurrent spectroscopy in single particle tracking?
This theme focuses on innovations in real-time feedback-driven single-particle tracking (RT-FD-SPT) algorithms and system components that achieve high spatiotemporal resolutions while allowing concurrent spectroscopic measurements of freely diffusing particles. The work addresses the trade-offs in feedback control, position estimation, and experimental parameters to realize in vivo single-molecule spectroscopy without tethering or immobilization artifacts.
2. How can particle filtering and Bayesian estimation frameworks enhance robustness and accuracy in 2D and 3D single particle and object tracking under complex conditions?
This research theme addresses the application of particle filtering (PF) and related Bayesian methods to improve tracking performance in single particle and object tracking tasks, including multitarget scenarios, visual tracking, and tracking in cluttered or occluded environments. It covers algorithmic advances to overcome challenges such as nonlinear dynamics, non-Gaussian noise, data association, occlusion recovery, and real-time constraints.
3. What advancements in 3D imaging modalities and illumination strategies enhance deep and high-resolution single particle tracking in scattering biological tissues?
Research in this area explores novel three-dimensional single particle tracking techniques that overcome limitations of depth penetration, temporal resolution, and signal-to-noise ratio inherent in conventional microscopy. Emphasis is on innovations in nonlinear and multiplexed excitation, dynamic laser spot scanning, and adaptions of two-photon microscopy to improve tracking fidelity deep inside scattering biological samples and multicellular environments.