Microscopy experiments have four key steps: (1) sample preparation, (2) microscope setup, (3) image acquisition, and (4) image analysis. Traditionally, these steps are done separately using generic methods, which can be inaccurate, inefficient, and wasteful because they are not tailored to specific biological problems and lack communication between steps.

The smart microscopy research in Bakshi laboratory combines experts in microscopy hardware and software, signal processing, and machine learning to create 'personalized' imaging solutions for specific biological problems/questions. In this approach, all steps interact, enabling the design and execution of smart microscopy experiments that are both data-efficient and accurate. Please follow Georgeos Hardo' blog (link) and our publications to learn more. The resource page contains links for the 'smart microscopy' hardware and software developed from our research.