Project title: Deep Learning for Quantum Dot Localization

Brief project description: This project combines artificial intelligence with hardware engineering to achieve nanometer-scale imaging precision. The primary focus is developing deep learning pipelines that process raw optical signals from quantum dot sensors, reconstructing the data to localize nanoscale emitters with high accuracy. To validate these neural network models against real-world data, the work also incorporates nanoscale wet-lab fabrication, including substrate preparation, quantum dot spin-coating and confocal microscopy analysis.