I am a CS Ph.D. student in the SAIL lab advised by Dr. Xintao Wu at the University of Arkansas.

My research focuses on trustworthy machine learning, with an emphasis on privacy and fairness. I mainly work on graph-structured data and large language models. I am also broadly interested in graph foundation models and applications of LLMs on graph data. Currently, I am also working on applications of graph machine learning in physical systems such as critical infrastructure networks.

📝 Preprints

Fair In-Context Learning via Latent Concept Variables[Paper]
Karuna Bhaila, Minh-Hao Van, Kennedy Edemacu, Chen Zhao, Feng Chen, Xintao Wu
ArXiV 2024
Soft Prompting for Unlearning in Large Language Models [Paper] [Code]
Karuna Bhaila, Minh-Hao Van, Xintao Wu
ArXiV 2024

📝 Publications

DP-TabICL: In-Context Learning with Differentially Private Tabular Data [Paper]
Alycia N. Carey*, Karuna Bhaila*, Kennedy Edemacu, Xintao Wu
Proceedings of 2024 IEEE International Conference on Big Data
Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach [Paper] [Code]
Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu
Proceedings of the 2024 SIAM International Conference on Data Mining (SDM)
*Also at NeurIPS 2023 Workshop New Frontiers in Graph Learning (GLFrontiers)
Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks [Paper] [Code]
Karuna Bhaila, Xintao Wu
Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN)
*Also at AAAI 2024 Workshop on AI to Accelerate Science and Engineering (AI2ASE)
Randomized Response Has No Disparate Impact on Model Accuracy [Paper] [Code]
Alycia N. Carey, Karuna Bhaila, Xintao Wu
Proceedings of 2023 IEEE International Conference on Big Data
Fair Collective Classification in Networked Data [Paper]
Karuna Bhaila, Yongkai Wu, Xintao Wu
Proceedings of 2022 IEEE International Conference on Big Data
*Also at KDD 2022 Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD)

🎖 Honors and Awards

Margaret Gerig Martin Graduate Scholarship
SIAM 2024 Student Travel Award
Reginald R. ‘Barney’ & Jameson A. Baxter Graduate Fellowship
College of Engineering Graduate Fellowship
Webster International Scholarship

💻 Experience

2019.05 - 2020.05: Data Analyst, Faculty Development Center at Webster University
2019.05 - 2019.07: Intern, Jenzabar

💬 Teaching

Lecturer, Python and Machine Learning
Multidisciplinary Bootcamp (MDaS), University of Arkansas, 2021 - 2024
Guest Lecturer, CSCE 4143 Data Mining
Undergraduate course, University of Arkansas, 2023
Math and CS Tutor
Webster University, 2019 - 2020

💻 Services

Conference Reviewer

International Conference on Machine Learning and Applications (ICMLA)
International Joint Conference on Neural Networks (IJCNN)

Journal Reviewer

Transactions on Big Data (TBD)
Human-Centric Intelligent Systems (HCIN)

Workshop Reviewer