Muhammad Rehan@muhammad_rehan_417
1
Events attended
1
Submissions made
Pakistan
1 year of experience
About me
I am a Computer Science student from Pakistan with a strong interest in Artificial Intelligence, Machine Learning, and Software Engineering. I enjoy building practical AI solutions that solve real-world problems and continuously explore emerging technologies through hands-on projects and hackathons. My experience includes developing machine learning applications such as an AI-powered Resume Analyzer and a deep learning-based thoracic disease classification system using the NIH ChestX-ray14 dataset. I have worked with Python, Scikit-learn, TensorFlow, and Streamlit while gaining experience in data preprocessing, model training, evaluation, and deployment. Beyond AI, I have a solid foundation in software development, data structures, algorithms, databases, and object-oriented programming. I believe in learning by building and enjoy collaborating with multidisciplinary teams to transform ideas into impactful products. I am passionate about innovation, continuous learning, and contributing to the global AI community through research, open collaboration, and competitive hackathons. My goal is to develop AI-driven technologies that create meaningful value for businesses and society.
🤝 Top Collaborators
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🤓 Latest Submissions
LeakLogic AI
LeakLogic AI is an explainable AI business-auditing platform built for small and medium-sized businesses that need to understand where profit is being lost. Users upload sales, refunds, supplier-cost, and inventory CSV files through a modern web dashboard. The FastAPI backend validates and normalizes the data, then runs four deterministic Python and pandas detectors for refund anomalies, discount leakage, supplier margin compression, and inventory drag. Each finding includes the affected entity, measured change, supporting evidence, confidence score, estimated dollar impact, likely cause, and recommended action. Findings are ranked by financial impact so decision-makers can focus on the most important issues first. After the calculations are completed, Fireworks AI transforms the verified structured findings into a concise executive narrative. The model is instructed not to invent figures, causes, evidence, or recommendations. If the AI service is unavailable, LeakLogic AI automatically returns a deterministic fallback summary, ensuring the audit still completes. The application is fully containerized with Docker and Docker Compose. The production frontend is deployed on Netlify, while the FastAPI backend is deployed on Vercel. The project uses Fireworks AI API access from the AMD hackathon ecosystem and was developed for the Unicorn Track as a product-focused AI solution. LeakLogic AI turns disconnected operational data into a clear answer to one business question: where are we quietly losing money, why does it matter, and what should we review next?
13 Jul 2026
