Data Mining
Machine Learning
Data Science
Adversarial Network
Large Language Model
Bio Medical Data Science
Big Data Analytics
Financial Machine Learning/Analytics
- Bioinformatics
- Computational Biology
- Machine Learning
- Bioinformatics and Computational Biology
- Machine Learning
- Pattern Recognition and Data Mining
Cloud Computing, Network Function Virtualization, Edge Computing
Data Science
Internet of Things
- Opportunistic Networks
- IoV, VANET
- Cryptography & Network Security
- Wireless Communications
- Wireless Sensor Networks & IoT
- Software Engineering
- Intelligent Systems
- Computer Vision
- Data Science
- Artificial Intelligence
- Machine Learning
- Field and Service Robotics
- Human Computer Interaction
His research spans Machine Learning, Deep Learning, and Computer Vision, with particular emphasis on the Fairness, Robustness, and Interpretability of Machine Learning Systems. He is currently investigating methods to ensure ML models are transparent, reliable, and equitable in real-world applications, with a focus on developing fair and interpretable algorithms for decision-critical domains.
Deep learning
- Machine Learning
- Neural Networks
- Digital Image Processing
- Transfer Learning
- Statistical Model in Machine Learning
- Software Engineering
- Image Processing
- Artificial Intelligence
Natural Language Processing, Explainable AI, Computational Linguistics
On Going Research Projects:
-Multimodal Idiomaticity Representation
-Text Domain Classification
-Figurative Language Understanding
-Low Resource Language
Blockchain, Machine Learning, AI and Computer Vision.
