• 🎓 BSc Biochemistry student with a growing love for AI in healthcare
• 🧠 Currently working on MAE-ViT models on retinal fundus images
• 🧬 Interested in bioinformatics, computational biology, and medical imaging
• 🐍 Writing most of my code in Python, mostly in Jupyter / VS Code
• 🎯 Goal: Build tools at the intersection of biology × AI

Custom MAE-ViT pipeline trained on retinal images (384×384).

• Patchify → masking → reconstruction with a custom PatchShuffle module
• Uses PyTorch, Albumentations, and MPS acceleration on Mac
• Visualizes masked inputs, reconstructions & attention behaviour
• Next step: use the encoder for retinal vessel segmentation
• Downstream Task: use the latent features with a U-Net style decoder and generate a binary mask

🔗 https://github.com/adityaasunil/MAESeg

• Deep Learning for medical imaging
• Segmentation architectures (UNet-style models)
• Fundamentals of bioinformatics & structural biology
• Statistics & ML foundations for scientific research

• Medical imaging / retina analysis projects
• ML projects in biology / healthcare
• Open-source Python tools for data or imaging

• Anything related to Computation x Life Sciences

⭐ Biology × Code × Curiosity