Karuna Bhaila
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Researcher
Also affiliated: University of Arkansas System (2025)
Unknown Researcher
Research Areas
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
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Privacy Protection in Machine Learning: Methods for Structured and Unstructured Data (2026)Journal of the Arkansas Academy of Science OpenAlex
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How Does Differential Privacy Affect Social Bias in LLMs? A Systematic Evaluation (2026)arXiv (Cornell University) OpenAlex
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Vulnerability Analysis of Integrated Power and Gas System Based on Influence Graph (2025)
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Fair In-Context Learning via Latent Concept Variables (2025)
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CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models (2025)
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Soft Prompting for Unlearning in Large Language Models (2025)
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DP-TabICL: In-Context Learning with Differentially Private Tabular Data (2024)
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Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks (2024)
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Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks (2024)
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Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach (2024)
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Randomized Response Has No Disparate Impact on Model Accuracy (2023)
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Fair Collective Classification in Networked Data (2022)
Collaboration Network
Top Collaborators
- Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach
- DP-TabICL: In-Context Learning with Differentially Private Tabular Data
- Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks
- Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks
- Soft Prompting for Unlearning in Large Language Models
Showing 5 of 8 shared publications
- Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach
- Fair Collective Classification in Networked Data
- DP-TabICL: In-Context Learning with Differentially Private Tabular Data
- Randomized Response Has No Disparate Impact on Model Accuracy
- DP-TabICL: In-Context Learning with Differentially Private Tabular Data
- Fair In-Context Learning via Latent Concept Variables
- Soft Prompting for Unlearning in Large Language Models
- Fair In-Context Learning via Latent Concept Variables
- Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach
- CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models
- Fair In-Context Learning via Latent Concept Variables
- Fair In-Context Learning via Latent Concept Variables
- Fair In-Context Learning via Latent Concept Variables
- Vulnerability Analysis of Integrated Power and Gas System Based on Influence Graph
- Vulnerability Analysis of Integrated Power and Gas System Based on Influence Graph
- Vulnerability Analysis of Integrated Power and Gas System Based on Influence Graph
- How Does Differential Privacy Affect Social Bias in LLMs? A Systematic Evaluation
- How Does Differential Privacy Affect Social Bias in LLMs? A Systematic Evaluation
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