Match tier Likely match
Presence Current · Arkansas
Last published 2025
Sources OpenAlex · ORCID
Refreshed 2026-08-15

Karuna Bhaila

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.

Researcher

Also affiliated: University of Arkansas System (2025)

Unknown Researcher

2 h-index 8 pubs 15 cited

Biography and Research Information

OverviewAI-generated summary

Karuna Bhaila's research investigates the application of advanced machine learning techniques, particularly graph neural networks and large language models, to address complex challenges in data privacy, security, and system reliability. Bhaila has explored methods for ensuring differential privacy in graph neural networks through reconstruction approaches and developed techniques for in-context learning with differentially private tabular data. Their work also addresses the prediction of cascading failures in power grids by utilizing node and edge attributed graph neural networks. Additionally, Bhaila has investigated approaches for unlearning in large language models and examined the impact of randomized response mechanisms on model accuracy and fairness in collective classification tasks within networked data. Bhaila has 8 publications and 13 citations, with an h-index of 2. Collaborations include work with Kennedy Edemacu, Alycia N. Carey, Aneesh Komanduri, and Xintao Wu, all from the University of Arkansas at Fayetteville.

Metrics

  • h-index: 2
  • Publications: 8
  • Citations: 15

Selected Publications

  • Privacy Protection in Machine Learning: Methods for Structured and Unstructured Data (2026)
    Journal of the Arkansas Academy of Science OpenAlex
  • How Does Differential Privacy Affect Social Bias in LLMs? A Systematic Evaluation (2026)
    arXiv (Cornell University) OpenAlex
  • Vulnerability Analysis of Integrated Power and Gas System Based on Influence Graph (2025)
  • Fair In-Context Learning via Latent Concept Variables (2025)
  • CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models (2025)
  • Soft Prompting for Unlearning in Large Language Models (2025)
    4 citations DOI OpenAlex
  • DP-TabICL: In-Context Learning with Differentially Private Tabular Data (2024)
    9 citations DOI OpenAlex
  • Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks (2024)
    4 citations DOI OpenAlex
  • Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks (2024)
    6 citations DOI OpenAlex
  • Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach (2024)
    Society for Industrial and Applied Mathematics eBooks 12 citations DOI OpenAlex
  • Randomized Response Has No Disparate Impact on Model Accuracy (2023)
    2 citations DOI OpenAlex
  • Fair Collective Classification in Networked Data (2022)
    2022 IEEE International Conference on Big Data (Big Data) 1 citation DOI OpenAlex

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Collaboration Network

15 Collaborators 7 Institutions 1 Country

Top Collaborators

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