I’m an engineering student focused on building practical AI systems in computer vision, machine learning, and automation. I enjoy implementing models from scratch and applying them to real-world problems.
• Currently working on: Multi-Agent Learning Simulation and AI automation
• Interests: Computer Vision, Reinforcement Learning, NLP systems
| Category | Tech / Tools |
|---|---|
| Languages | Python, C++, SQL |
| AI / ML | PyTorch, TensorFlow, Scikit-Learn |
| Computer Vision | OpenCV, YOLOv8, MediaPipe |
| NLP & RAG | LangChain, HuggingFace |
| Tools | Git, Docker, Linux, Streamlit, Jupyter |
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Real-Time Sign Language Recognition - Real-time LSTM based system that detects and interprets sign language gestures using computer vision and sequence models.
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HandGestureAutomation - Control your computer using hand tracking and gesture recognition through a webcam.
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RAG Multi-File Question Answering - Retrieval-augmented generation pipeline that answers questions across PDFs, DOCX, CSV and text files.
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FlappyBird Genetic AI (NEAT) - Neural networks evolved using the NEAT algorithm that learn to play Flappy Bird autonomously.
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Crowd Detection System - YOLOv8 based real-time crowd detection and tracking with proximity analysis.
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Multi-Agent Learning Simulation (Work in Progress) - Research-oriented simulation where multiple agents learn and interact inside an evolving environment.
Currently seeking collaboration on research projects and open source work in AI, machine learning, and computer vision.