I'm an AI Engineer & Independent Researcher focused on building intelligent systems that operate reliably under real-world constraints.

My work spans:

• 🧠 Multimodal Artificial Intelligence
• 🩺 Medical AI Systems
• 📜 Sanskrit NLP & Low-Resource Language AI
• 🌍 Explainable AI (XAI)
• ⚡ Edge Intelligence & Efficient AI

I enjoy combining research with engineering to create deployable AI systems that move beyond experiments into practical applications.

• Explainable Artificial Intelligence (XAI)
• Multimodal Learning
• Medical Imaging AI
• Sanskrit Natural Language Processing
• Time-Series Forecasting
• Edge AI & Efficient Inference
• Deep Learning Systems
• Intelligent Environmental Monitoring

Explainable deep learning framework for forecasting industrial atmospheric pollutants using SHAP-based interpretability.

• SHAP-based explainability
• Multi-city AQI forecasting
• Hybrid deep learning architectures
• Research-focused implementation

🔗 Project Website: https://akashnathai.github.io/hybrid_aqi_xai/

🔗 GitHub Repository: https://github.com/akashnathai/hybrid_aqi_xai

Deep learning pipeline for generating Sanskrit captions from images using CNN-LSTM architectures.

• Low-resource NLP
• Sanskrit language modeling
• Vision-language learning
• Multimodal AI

Research on intelligent medical imaging systems for MRI-based analysis and classification.

• Deep learning for healthcare
• Medical imaging pipelines
• Explainable healthcare AI
• Clinical intelligence systems

• Efficient Multimodal AI
• Explainable AI for Time-Series Systems
• Sanskrit Vision-Language Models
• Edge AI Optimization
• Reliable AI Systems