Mohammed Mudassir Uddin is the Founder at Auragenzy, with prior experience as a Machine Learning Engineer at TechieYan Technologies. He holds education from Muffakham Jah College of Engineering & Technology (MJCET), Osmania University, and the State Board of Technical Education and Training (SBTET), Telangana, focusing on Computer Science and Computer Science Engineering. His tinkerer projects include building full-stack prototypes like YatraKavach (TypeScript/React) and TradeGenie (Python/FastAPI), alongside developing ML models (XGBoost, transfer learning, DNABERT-style) for computer vision and medical prediction via MediCoach.

Machine Learning, Deep Learning, Prompt Engineering, Full-Stack integrations, Computer Vision, Data Science

Building full-stack prototypes like YatraKavach (TypeScript/React frontend) and TradeGenie (Python/FastAPI backend). Developing ML models (XGBoost, transfer learning, DNABERT-style) for computer vision and medical prediction (MediCoach), demonstrating integration of deep learning and prompt engineering techniques into web applications.

Mohammed Kaif Pasha is a Computer Science Engineering student passionate about AI, full-stack development, and building impactful tech solutions. He has worked on innovative projects like AI-powered traffic management and platforms empowering rural entrepreneurs. With strong problem-solving skills and a drive to learn, he aims to become a top software engineer in a leading MNC.

I am interested in Artificial Intelligence, Computer Vision, and full-stack web development. I aim to explore scalable AI solutions for transportation, security, and social impact. I am looking to learn more about cloud technologies, product development, and startup ecosystems. I’m open to collaborating with innovators, developers, and mentors who are passionate about building technology that solves real-world problems.

I’m currently working on a pest detection system using few-shot learning, where the model can identify pests with very limited training images. The goal is to help farmers detect crop issues early using camera-based monitoring. I’m experimenting with different AI models to improve accuracy and adaptability for real-world agricultural environments.