Machine Learning-based methodology for understanding phytoplankton cell morphology

I use advanced computer techniques to analyze phytoplankton's internal and external structures. These microscopic organisms play a crucial role in ocean ecosystems and are vital indicators of environmental changes, such as climate change and pollution. However, traditional methods for studying them are limited to specific types, which poses a challenge. I aim to pioneer innovative approaches that transcend these limitations and enable compelling study of diverse phytoplankton species. Additionally, I aim to extend this methodology to encompass a broader range of oceanic organisms. Ultimately, my work aims to deepen our understanding of marine ecosystems and contribute to environmental conservation efforts.