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Projects

Here are some of the key projects I've worked on, showcasing my expertise in AI, machine learning, and software engineering.

🩺 AskDoc

Symptom-based Disease Recommendation System

An intelligent health assistant that analyzes symptoms and provides preliminary disease recommendations using machine learning algorithms.

Tech Stack: Python, TensorFlow, NLP, Medical Data APIs Impact: Helps users get initial health insights before consulting healthcare professionals

🎵 Emosong

Emotion-based Music Recommendation

A music recommendation system that analyzes user emotions and suggests songs that match their current mood using sentiment analysis and collaborative filtering.

Tech Stack: Python, PyTorch, Spotify API, Sentiment Analysis Features: Real-time emotion detection, personalized playlists, mood tracking

🤖 LLM-Gym

Search and Chat Tool

A comprehensive platform for testing and comparing different large language models in search and conversational contexts.

Tech Stack: Python, Langchain, Multiple LLM APIs, Vector Databases Purpose: Benchmarking LLM performance for various use cases

🦟 Malaria Detection

Transfer Learning for Medical Diagnosis

A computer vision system that detects malaria parasites in blood cell images using transfer learning techniques.

Tech Stack: Python, TensorFlow, Computer Vision, Transfer Learning Achievement: High accuracy in parasite detection, potential for field deployment

🤟 Sign Language Detection

Real-time Sign Language Recognition

A computer vision system that recognizes sign language gestures in real-time, making communication more accessible.

Tech Stack: Python, OpenCV, Deep Learning, Real-time Processing Impact: Improving accessibility for deaf and hard-of-hearing communities

Production Systems

🗣️ Voice Assistant Platform

Enterprise Voice AI Solution

Built high-precision voice assistants for enterprise clients with 97% accuracy in intent recognition.

Key Features: - Real-time speech processing - Custom wake word detection - Multi-language support - Integration with business systems

💳 Transaction Tagging Engine

Financial Data Classification

Developed an AI system for automatically categorizing financial transactions with 95% F1 score.

Technical Highlights: - Natural language processing for transaction descriptions - Machine learning classification models - Real-time processing pipeline - Integration with banking systems

Open Source Contributions

I actively contribute to the AI community through open-source projects and tools that help other developers build better AI systems.

Areas of Contribution

  • RAG Systems: Tools for retrieval-augmented generation
  • LLM Utilities: Helper libraries for working with language models
  • AI Infrastructure: Deployment and monitoring tools
  • Educational Resources: Tutorials and documentation

Future Projects

I'm constantly exploring new ideas and technologies. Some areas I'm excited to work on include:

  • Multimodal AI: Combining text, vision, and audio processing
  • Edge AI: Deploying AI models on resource-constrained devices
  • AI Safety: Building more reliable and safe AI systems
  • Conversational AI: Next-generation chatbots and virtual assistants

Interested in collaborating on any of these projects? Let's connect!