Match tier
Likely match
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-10-08
K
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.
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2 h-index
13 pubs
23 cited
Research Areas
Biography and Research Information
OverviewAI-generated summary
Karuna Bhaila's research focuses on the intersection of machine learning, data privacy, and fairness in artificial intelligence systems. Their work investigates methods to protect sensitive information within machine learning models, particularly in the context of graph neural networks and large language models. Recent publications explore techniques like local differential privacy for graph data reconstruction and in-context learning with differentially private tabular data. Bhaila has also studied the prediction of cascading failures in power grids using graph neural networks and the implications of randomized response on model accuracy. Collaborative efforts include work with Xintao Wu, Minh-Hao Van, Kennedy Edemacu, and Alycia N. Carey at the University of Arkansas at Fayetteville, resulting in multiple shared publications.
Metrics
- h-index: 2
- Publications: 13
- Citations: 23
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
Xintao Wu
University of Arkansas at Little Rock
8 shared publications
In database
- 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
Yongkai Wu
Clemson University (US)
2 shared publications
- Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach
- Fair Collective Classification in Networked Data
Alycia N. Carey
University of Arkansas at Fayetteville
2 shared publications
In database
- DP-TabICL: In-Context Learning with Differentially Private Tabular Data
- Randomized Response Has No Disparate Impact on Model Accuracy
Kennedy Edemacu
University of Arkansas at Fayetteville
2 shared publications
In database
- DP-TabICL: In-Context Learning with Differentially Private Tabular Data
- Fair In-Context Learning via Latent Concept Variables
Minh-Hao Van
University of Arkansas at Fayetteville
2 shared publications
In database
- Soft Prompting for Unlearning in Large Language Models
- Fair In-Context Learning via Latent Concept Variables
Wen Huang
University of Arkansas at Fayetteville (US)
1 shared publication
- Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach
Aneesh Komanduri
University of Arkansas at Little Rock
1 shared publication
In database
- CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models
Chen Zhao
Baylor University (US)
1 shared publication
- Fair In-Context Learning via Latent Concept Variables
Feng Chen
The University of Texas at Dallas (US)
1 shared publication
- Fair In-Context Learning via Latent Concept Variables
Xintao Wu
University of Arkansas at Fayetteville
1 shared publication
In database
- Fair In-Context Learning via Latent Concept Variables
Nof Yasir
North Dakota State University (US)
1 shared publication
- Vulnerability Analysis of Integrated Power and Gas System Based on Influence Graph
Di Wu
North Dakota State University (US)
1 shared publication
- Vulnerability Analysis of Integrated Power and Gas System Based on Influence Graph
Ying Huang
North Dakota State University (US)
1 shared publication
- Vulnerability Analysis of Integrated Power and Gas System Based on Influence Graph
Eduardo Tenorio
University of Arkansas at Fayetteville
1 shared publication
In database
- How Does Differential Privacy Affect Social Bias in LLMs? A Systematic Evaluation
Xintao Wu
University of Arkansas at Fayetteville
1 shared publication
In database
- How Does Differential Privacy Affect Social Bias in LLMs? A Systematic Evaluation
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