Aoinyom Mohan

I’m a freshly graduated ECE student from Assam University, and my work has resulted in two Springer Nature LNCS medical AI papers accepted (undergraduate level) and a third IEEE conference paper under review. My focus is deep learning for medical imaging, where I turn research ideas into models that can actually help clinical decision-making.

I build hybrid and attention-based architectures for tasks like gallbladder cancer classification and retinal multi-disease classification, including Vision Transformer modeling on fundus images. I’ve achieved strong benchmark results (e.g., 95% binary accuracy and 91% three-class accuracy on the GBCU dataset) and added explainability components like Grad-CAM and fusion of clinical metadata using FiLM conditioning.

Alongside my degree, I spent four years in professional video production, which shaped how I communicate, handle feedback, and deliver on schedule. I bring that same discipline to research and engineering—clear writing, careful experimentation, and reliable, production-ready Python code.