Research
Optimizing Computational Resource Requirements in Large Language Models
This ongoing research focuses on developing novel techniques to optimize the computational resources required for training and deploying large language models. The goal is to make these powerful AI tools more accessible and efficient for a wider range of applications.
Key Areas of Investigation:
- Model compression techniques
- Efficient attention mechanisms
- Distributed training strategies
- Adaptive resource allocation
AI-Powered COVID-19 Diagnosis from X-Ray Images
This project focuses on developing deep learning models to identify COVID-19 from chest X-ray images. The system aims to provide accurate diagnostic predictions while being designed for research and educational purposes, leveraging cutting-edge AI methodologies.
Key Areas of Investigation:
- Deep learning for medical imaging
- Convolutional neural networks (CNNs)
- Interactive tools using Streamlit
- Ethical use of AI in healthcare diagnostics