Match tier Likely match
Presence Current · Arkansas
Last published 2026
Sources OpenAlex · ORCID
Refreshed 2026-08-16

Sunanda Das

This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.

Graduate Research Assistant

Graduate Student Researcher

14 h-index 77 pubs 1,303 cited

  • Diabetes Mellitus
  • Hypertension
  • Adult
  • Bangladesh
  • Cross-Sectional Studies
  • Female
  • Humans
  • Male
  • Obesity
  • Thinness
  • Comorbidity
  • Prevalence
  • Overweight

Biography and Research Information

OverviewAI-generated summary

Sunanda Das's research focuses on the application of machine learning and deep learning techniques to address challenges in various domains, including healthcare, cloud computing, intelligent vehicles, and financial markets. Her work has explored the impact of missing value imputation on machine learning model performance and developed hybrid approaches for complex tasks. Das has investigated the prediction of CPU workload in cloud virtual machines using Bi-LSTM based recurrent neural networks and the estimation of road boundaries for intelligent vehicles using DeepLabV3+ architecture. Her publications also include stock price prediction models utilizing Bi-LSTM and GRU, and flood prediction in Bangladesh using the k-Nearest Neighbors algorithm. Additionally, she has examined the association of obesity with hypertension and diabetes in adults in Bangladesh and explored smartphone-based non-invasive hemoglobin level estimation. Das holds a h-index of 14 with 77 total publications and 1,303 total citations.

Metrics

  • h-index: 14
  • Publications: 77
  • Citations: 1,303

Selected Publications

  • DiSec: Mitigating Backdoors in Pre-trained Language Models via Disentanglement of Adversarial Weights for Secure Fine-Tuning (2026)
    Underline Science Inc. DOI OpenAlex
  • DiSec: Mitigating Backdoors in Pre-trained Language Models via Disentanglement of Adversarial Weights for Secure Fine-Tuning (2026)
  • DL$^3$M: A Vision-to-Language Framework for Expert-Level Medical Reasoning through Deep Learning and Large Language Models (2025)
    arXiv (Cornell University) DOI OpenAlex

View all publications on OpenAlex →

Collaboration Network

95 Collaborators 23 Institutions 6 Countries

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