I am a Software Engineer and Graduate Student at Northeastern University with a deep interest in building scalable applications and intelligent systems. My expertise lies at the intersection of Full-Stack Development (Django/Vue) and Applied AI (LLMs, Neural Networks, RAG).
- 🎓 Currently: Focused on Machine Learning and Large Language Model architectures.
- 💡 Core Strengths: Designing modular software, optimizing data pipelines, and implementing AI agents from scratch.
- 🤝 Collaborations: I’m always open to working on innovative Django or AI-driven open-source projects.
- 📫 Reach me at: mulerishi1234@gmail.com
- ArXiv Intelligence MCP | Python, RAG, ChromaDB
- An intelligence server that uses RAG to query ArXiv papers. Features semantic memory using ChromaDB and PDF-to-Markdown ingestion for clean LLM context.
- AI-GovBot | Python, LLMs, RAG
- A specialized chatbot leveraging the AGORA dataset to help organizations navigate complex AI governance and regulatory frameworks.
- MNIST Neural Network from Scratch | Python, NumPy
- Built a modular neural network architecture from the ground up for digit recognition, including custom backpropagation and optimization logic.
- Chess AI Agent | Python, Minimax
- A Python-based chess engine with a Minimax AI opponent, implementing alpha-beta pruning and comprehensive unit testing for move validation.
- Django Learning Management System | Django, Azure, Bootstrap
- A full-scale LMS supporting teacher/student roles, course management, and cloud-hosted storage. Deployed on Microsoft Azure.
- Personalized Tourism Recommender | JavaScript, Python, APIs
- An interactive chatbot-based recommender system that provides real-time map-based suggestions for tourists using climate and environmental data.
- Stock/Inventory Management System | Django, MySQL
- A robust department-level automation tool for tracking asset movement and automated low-stock notifications.
"Simplicity is the soul of efficiency."