Translated research papers into code, trained Diffusion models, and contributed to research and development in this area. I am working on Denoising Diffusion Probabilistic Models (DDPM) and Stable Diffusion, leveraging diffusion models and super-resolution techniques for the detection of diabetic retinopathy. My focus is on applying these advanced methods to image segmentation, enhancing the precision and accuracy of retinal image analysis, and contributing to more effective diagnostic tools in medical imaging.

I successfully completed a Data Science internship, where I developed several small-scale Data Science projects. These projects were focused on solving specific real-world problems, allowing me to apply my skills in data analysis, model building, and performance evaluation. This experience enhanced my practical understanding of machine learning and its applications in various domains.