NCBI Gene MCP Client

Model Context Protocol (MCP) client integrating with NCBI Entrez API for gene and protein metadata retrieval.

  • Symbol-based queries & flexible search with dual interfaces (REST API + CLI)
  • Production-ready MCP server (JSON-RPC) compliant with NCBI rate-limiting
  • Deployed on Vercel with modular design and automated testing
Python FastAPI Bootstrap Jinja2 REST
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Skill Lyft: AI-Powered Learning Prototype

Learning platform simplifying complex ML concepts like Transformers, LLMs, and Neural Networks.

  • Full-stack prototype with React frontend and Flask backend
  • User testing with 20+ students in Agile 4-person workflow
  • 30% improvement in navigation efficiency after usability testing
Figma React Flask Hugging Face PyTorch
Figma Prototype
UniChatbot

LLM-powered chatbot using LangChain and RAG to answer 500+ university-related queries.

  • Semantic search with vector embeddings, improving query relevance by 35%
  • Optimized local inference with HuggingFace models and dynamic context windows
  • Containerized with Docker and deployed via Streamlit
Python LangChain RAG ChromaDB Streamlit
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Smart StudyDesk: AI-Powered Study Organizer

Cross-platform study assistant that organizes lecture notes, summarizes content, and generates personalized quizzes.

  • Usability testing with 20+ students using NASA-TLX workload analysis
  • Improved navigation efficiency by 30% after iterative refinements
  • Semi-structured interviews for user feedback
Figma UI/UX Research Python
Figma Prototype
Zero-Shot Medical Image Classification with CLIP

Comparative study of CLIP against Vision Transformers (ViT) and ResNet50 for OCT medical image classification.

  • Zero-shot classification with custom prompts
  • Evaluated with Precision, Recall, F1, ROC-AUC, and MCC metrics
  • Validated on OCT2017 and RFMiD datasets
Python PyTorch CLIP ViT ResNet50
HealthSenseAI: Automated Disease Detection

MERN stack web app with Hugging Face pre-trained model for automated disease predictions.

  • End-to-end ML pipeline for preprocessing, inference, and deployment
  • Leveraged Gradio to cut prototyping cycles by 40%
  • User-friendly interface for non-technical healthcare staff
MongoDB Express React Node Python
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Efficient Model for Concrete Cracks Detection

Deep learning models for architectural infrastructure crack detection using knowledge distillation.

  • Trained and benchmarked 9 CNN architectures on SDNET2018 dataset (56k+ images)
  • Applied KD to compress ResNet152/DenseNet into lightweight models
  • Improved MCC by up to 20% with Grad-CAM interpretability
Python TensorFlow Keras
Automated Face Recognition Attendance System

Real-time face recognition system using Haar cascade and OpenCV processing 200+ students per session.

  • Deployed in Flask web app for remote access
  • Reduced attendance processing time by 80%
Python OpenCV Flask
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Climate Change Forecast of Delhi

SARIMAX forecasting models on 20+ years of regional climate data to predict seasonal and long-term trends.

  • Preprocessed climate time-series data (1.6B+ records, Berkeley Earth)
  • Extracted Delhi-specific subsets for regional analysis
  • Interpretable visual analytics showing warming trends
Python Scikit-learn Matplotlib Seaborn
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