Sunanda Das Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Graduate Research Assistant

University of Arkansas at Fayetteville

grad_student

14 h-index 77 pubs 1,289 cited

Research Areas

Advanced Neural Network Applications Machine Learning Applications Health Disparities and Outcomes Meta-analysis and Systematic Reviews Diet and Metabolism Studies Behavioral and Psychological Studies Natural Language Processing Techniques

Links

ORCID Lab Website

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OverviewAI-generated summary

Sunanda Das's research interests lie in the application of machine learning and deep learning techniques to address diverse challenges. Her work includes developing hybrid models for Bangla sign language recognition, utilizing deep transfer learning with random forest classifiers. She has investigated novel deep learning architectures, such as Bi-LSTM based hybrid recurrent neural networks, for predicting cloud virtual machine CPU workload and for stock price prediction. Das has also explored the use of machine learning algorithms like k-Nearest Neighbors for flood prediction in Bangladesh and deep learning for road boundary estimation in intelligent vehicles. Her research extends to health-related applications, including the association of overweight and obesity with chronic conditions in adults and non-invasive hemoglobin level estimation using smartphone technology. Das holds a scholar metric of 14 for her h-index and has published 77 papers, accumulating over 1,289 citations.

Metrics

h-index: 14
Publications: 77
Citations: 1,289

Selected Publications

Applications of waste Tulsa Plant Ash for improved cement properties and environmental conservation (2025) DOI
Enhanced Brain Tumor Classification Using HyperLSTM and EfficientNetB0 Integration for Accurate Diagnostics (2025) DOI
Non-invasive Haemoglobin Estimation from Nail Pallor Leveraging Pre-trained Models and Graph Neural Networks (2025) DOI
Attention enabled precise haemoglobin prediction: A GNN based non-invasive approach (2025) DOI
MoE-TTA: Enhancing Continual Test-Time Adaptation for Vision-Language Models through Mixture of Experts (2024) DOI
Next-Gen Heart Disease Prediction: A Gradient Boosting Approach with L1-Regularized Neural Networks (2024) DOI
Investment Tourism in Global Investment (2024) DOI
THE USE OF ARTIFICIAL INTELLIGENCE FOR FOLKSTHROUGHINCAPACITY: A CHEERFULTHENTALENTEDUPCOMINGFAST (2024) DOI
DIA-VXNET: A framework for automated diabetic eye disease detection using transfer learning with feature fusion network (2024) DOI
InfLocNet: Enhanced Lung Infection Localization and Disease Detection from Chest X-Ray Images Using Lightweight Deep Learning (2024) DOI
An Ensemble Technique Using Genetic Algorithm and Deep Learning for the Prediction of Rice Diseases (2024) DOI
Multi-scale Vision Transformer toward improved non-invasive anaemia detection using palm video (2024) DOI
TREATED WASTE WATER USE IN CONSTRUCTION INDUSTRIES (2024) DOI
DeepRegYLab: A Dilated Convolution and Network Design Space Based Image Segmentation Model to Segment Healthy GI Tract of Cancer Patients to Automate Radiotherapy (2024) DOI
Enhancing E-Learning: EEG Signal Classification to Evaluate Students' Understanding of Online Lectures (2024) DOI