Pranshu Saini

🎓 I'm a passionate and driven Computer Science undergraduate at Bennett University with a strong foundation in C++, Python, Java, and machine learning. With hands-on experience in real-world applications, I’ve developed intelligent systems for disease detection (including diabetic retinopathy and Alzheimer's) using CNNs, transfer learning, and explainable AI techniques like Grad-CAM.

🚀 I’ve built impactful projects like DocPat, a diagnostic web platform powered by ML algorithms, and an ISL Converter, which enhances accessibility for the hearing-impaired using real-time ISL image/text conversion. My technical toolkit includes Django, Flask, TensorFlow, and data tools like SQL and Power BI.

💼 During my internship at Bennett University, I developed a CNN-based machine learning model for early detection of diabetic retinopathy. I worked on preprocessing large-scale retinal image datasets, fine-tuning deep learning architectures, and improving model accuracy through transfer learning.

🏆 I'm also a Smart India Hackathon 2024 finalist and hold NCC Certificate A, reflecting both my technical acumen and leadership discipline.

📚 Always eager to learn, build, and collaborate — whether it's tackling 130+ LeetCode problems or exploring innovations at the intersection of healthcare and AI.

Developed a machine learning model to detect diabetic retinopathy using convolutional neural networks (CNNs) and transfer learning. Analyzed retinal images, tuned models, and managed large datasets to enhance detection accuracy.

currently pursuing my last year of B.tech from bennett university in data science