Md Rizwanul Kabir Source Confirmed

OverviewAI-generated summary

Md Rizwanul Kabir's research focuses on the application of deep learning and transformer-based models to address complex problems across various domains. His work includes developing robust hybrid deep learning models for financial time series forecasting and creating ensemble-based approaches for detecting COVID-19 using chest X-ray images. Kabir has also investigated the analysis of EEG signals for emotion recognition and the use of deep learning with hyperparameter tuning for sentiment analysis from audio datasets. His recent work extends to transformer-based generative adversarial networks for speed-of-sound reconstruction in medical imaging, as well as GPU-accelerated imaging techniques. Additionally, he has explored entity resolution using transformers for synthetic datasets. Kabir collaborates with researchers such as Mariofanna Milanova and Md. Samin Morshed at the University of Arkansas at Little Rock.

Metrics

• h-index: 4
• Publications: 9
• Citations: 93