Aidong Zhang
Thomas M. Linville Professor
Computer Science, Biomedical Engineering, and Data Science
About
Aidong Zhang's research focuses on developing machine learning approaches to interpretable and fair learning, concept-based learning, federated learning, and generative AI. She also works on large language models for hypothesis generations for scientific discovery. Dr. Zhang is Thomas M. Linville Professor of Computer Science, with a joint appointment in the Department of Biomedical Engineering and School of Data Science at University of Virginia. Her research interests focus on machine learning, data mining, bioinformatics and health informatics.
Note: My lab has position available for creative PhD students, motivated for doing research in the areas of machine learning, data mining, bioinformatics, and health informatics. If you are interested, please contact me.
Research Interests
Machine Learning
Data Mining
Bioinformatics
Health Informatics
Selected Publications
FedMBridge: Bridgeable Multimodal Federated Learning,International conference on machine learning (ICML2024), Vienna, Austria, July 21-27, 2024 (oral presentation)
Jiayi Chen and Aidong Zhang
Benchmarking Spurious Bias in Few-Shot Image Classifiers, the 18th European Conference on Computer Vision (ECCV2024), Sep 29th - Oct 4th, 2024, Milano, Italy.
Guangtao Zheng, Wenqian Ye, Aidong Zhang
Benchmarking Retrieval-Augmented Generation for Medicine, the ACL Findings, 2024.
Guangzhi Xiong, Qiao Jin, Zhiyong Lu, and Aidong Zhang
CoLiDR: Concept Learning using Aggregated Disentangled Representations, Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Barcelona, Spain, August 25-29, 2024.
Sanchit Sinha, Guangzhi Xiong, and Aidong Zhang
On the Role of Server Momentum in Federated Learning, AAAI 2024
Jianhui Sun, Xidong Wu, Heng Huang, Aidong Zhang
On Disentanglement of Asymmetrical Knowledge Transfer for Modality-task Agnostic Federated Learning, AAAI 2024
Jiayi Chen and Aidong Zhang
AdvST: Revisiting Data Augmentations for Single Domain Generalization, AAAI 2024
Guangtao Zheng, Mengdi Huai, Aidong Zhang
Solving a Class of Non-Convex Minimax Optimization in Federated Learning, NeurIPS 2023
Xidong Wu, Jianhui Sun, Zhengmian Hu, Aidong Zhang, Heng Huang
Federated Conditional Stochastic Optimization, NeurIPS 2023
Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang, Heng Huang
On Hierarchical Disentanglement of Interactive Behaviors for Multimodal Spatiotemporal Data with Incompleteness, Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2023), Long Beach, CA, USA, August 6-1
Jiayi Chen and Aidong Zhang
Enhance Diffusion to Improve Robust Generalization, Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2023), Long Beach, CA, USA, August 6-10, 2023
Jianhui Sun, Sanchit Sinha, Aidong Zhang
Understanding and Enhancing Robustness of Concept-based Models, the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-2023)
Sanchit Sinha, Mengdi Huai, Jianhui Sun, Aidong Zhang
CLEAR: Generative Counterfactual Explanations on Graphs, NeurIPS 2022 Conference, New Orleans, November 28 -- December 9, 2022
Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li
Towards Automating Model Explanations with Certified Robustness Guarantee, Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2022), Vancouver Convention Centre, Canada, Feb 21-28, 2022
Mengdi Huai, Jinduo Liu, Chenglin Miao, Liuyi Yao, Aidong Zhang
Demystify Hyperparameters for Stochastic Optimization with Transferable Representations, Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2022)
Jianhui Sun, Mengdi Huai, Kishlay Jha, and Aidong Zhang
FedMSplit: Correlation-Adaptive Federated Multi-Task Learning across Multimodal Split Networks, Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2022)
Jiayi Chen and Aidong Zhang
Towards Automating Model Explanations with Certified Robustness Guarantee, Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2022)
Mengdi Huai, Jinduo Liu, Chenglin Miao, Liuyi Yao, Aidong Zhang
Malicious Attacks against Deep Reinforcement Learning Interpretations, the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020)
Mengdi Huai, Jianhui Sun, Renqin Cai, Liuyi Yao and Aidong Zhang
Towards Interpretation of Pairwise Learning, the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20)
Mengdi Huai, Di Wang, Chenglin Miao, Aidong Zhang
CorNet: Correlation Networks for Extreme Multi-label Text Classification, the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020)
Guangxu Xun, Kishlay Jha, Jianhui Sun and Aidong Zhang
Task-Adaptive Graph Meta-learning, the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020)
Qiuling Suo, Jingyuan Chou, Weida Zhong and Aidong Zhang
HGMF: Heterogeneous Graph-based Fusion for Multimodal Data with Incompleteness, the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020)
Jiayi Chen and Aidong Zhang
Pairwise Learning with Differential Privacy Guarantees, the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20)
Mengdi Huai, Di Wang, Chenglin Miao, Jinhui Xu, Aidong Zhang
Metric Learning on Healthcare Data with Incomplete Modalities, the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China, August 10-16, 2019
Qiuling Suo, Weida Zhong, Fenglong Ma, Ye Yuan, Jing Gao, and Aidong Zhang
Hypothesis Generation From Text Based On Co-Evolution Of Biomedical Concepts, the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2019), Alaska, USA, August 4-8, 2019
Kishlay Jha, Guangxu Xun, Yaqing Wang, and Aidong Zhang
Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm, the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China, August 10-16, 2019
Mengdi Huai, Hongfei Xue, Chenglin Miao, Liuyi Yao, Lu Su, Changyou Chen, and Aidong Zhang
Representation Learning for Treatment Effect Estimation from Observational Data, Thirty-second Conference on Neural Information Processing Systems (NIPS2018), Montréal, Canada, December 3-8, 2018
Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, and Aidong Zhang
Concepts-Bridges: Uncovering Conceptual Bridges Based on Biomedical Concept Evolution, the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2018), London, UK, August 19-23, 2018
Kishlay Jha, Guangxu Xun, Yaqing Wang, Vishrawas Gopalakrishnan, and Aidong Zhang
Awards
Thomas M. Linville Endowed Professorship
2023
Fellow -- American Institute for Medical and Biological Engineering (AIMBE)
2021
ACM Fellow
2017
IEEE Fellow
2009
SUNY Distinguished Professor
2014
UB Distinguished Professor
2012
National Science Foundation CAREER Award
1998
Featured Grants & Projects
NSF Project
An Explainable Machine Learning Platform for Single Cell Data Analysis
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NSF Project
Collaborative Research: PPoSS: Co-designing Hardware, Software, and Algorithms to Enable Extreme-Scale Machine Learning Systems
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NSF Project
A Scalable Hardware and Software Environment Enabling Secure Multi-party Learning
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NSF Project
Knowledge-Guided Meta Learning for Multi-Omics Survival Analysis
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NSF: project
NSF: Collaborative Research: Mining and Leveraging & Knowledge Hypercubes for Complex Applications
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NSF HDR Project
Collaborative Research: Knowledge Guided Machine Learning: A Framework for Accelerating Scientific Discovery
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NSF Project
Multimodal Machine Learning for Data with Incomplete Modalities
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UVA’s 2024 Research Achievement Awards Feature Numerous Engineering Faculty
Read NowFive engineering faculty won three of the University of Virginia’s top research awards. Many more were recognized during an annual ceremony celebrating UVA’s research accomplishments.
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Community Servers: Largest Computing Society Says 2 UVA Profs Among 7 Best
Read NowThe Association for Computing Machinery, or ACM, recognized computer scientists Aidong Zhang and Jack Davidson for above-and-beyond service to the organization and their field.
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Celebrating UVA Women Engineers at the Forefront of Health Care Advancements
Read NowWe take pride in the many innovative researchers among our faculty. Join us in celebrating some of the women who contribute to our school and community, shaping the future of engineering.