Automatic behavior clustering of freely moving invertebrates through 3D imaging

In this project, we develop advanced imaging techniques to better understand animal behavior in their natural environments. To achieve this, we propose: (i) customized light-sheet microscopy (LSM) hardware and software tailored for imaging small animals in the wild, (ii) mathematical algorithms designed to capture images in cluttered or complex media, and (iii) computational models to analyze and interpret behavioral patterns from the acquired data. Our work explores compressive sensing and machine learning algorithms, which have recently shown significant promise in addressing these challenges.