About
I engineer and deploy AI solutions - ranging from multimodal embeddings and real-time voice-interactive agents to intelligent document analysis systems.
My work spans across domains including computer vision, natural language processing, and agentic AI, with impactful applications.
I build on top of open-source technologies such as PyTorch, OpenCV, Streamlit, and HuggingFace, incorporating frameworks like CLIP, custom ResNet-like models, and retrieval-augmented pipelines.
I am particularly driven by solving real-world problems through scalable, efficient, and user-centric AI solutions that improve productivity and decision-making.
Projects
PyTorch
Bird Species Classification
A CNN based approach featuring Residual connections for Bird Species Classification.
Python, OpenAI-CLIP
Zeta DB
A Python-based multimodal vector database designed to store and search for images and text using their semantic embeddings.
Python, Streamlit, OpenAI, Gemini, Groq
ANOTAR
Leverage the power of LLMs to convert PDFs/Images to Markdown Notes
Python, OpenCV, Mediapipe, Flask
Real-time Human Pose Estimation
Perform real-time human pose estimation from a live webcam feed.
PyTorch
Stock Price Prediction
A Hybrid BiGRU-LSTM Neural Network for multivariate time-series prediction
Education
2022 - Present
Electrical Engineering (B.Tech)
Indian Institute of Technology, Delhi
Working on embedded systems and machine learning.
2012 - 2022
10 + 2 (Science)
Delhi Public School, Durgapur
Excelled in academics and coding competitions.
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Karan Burnwal | 2025