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, generative AI and medical applications, such as diagnosis and monitoring of Alzheimer's Disease (AD) and AD-related dementias (ADRD). 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
Concept‑RuleNet: Grounded Multi‑Agent Neurosymbolic Reasoning in Vision Language Models, The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 26), Singapore, January 20 – January 27, 2026. (Oral)
Sanchit Sinha, Guangzhi Xiong, Zhenghao He, Aidong Zhang
Rectifying Shortcut Behaviors in Preference-based Reward Learning,
NeurIPS 2025, San Diego, Dec 2-7, 2025. Wenqian Ye, Guangtao Zheng, Aidong Zhang
NeurIPS 2025, San Diego, Dec 2-7, 2025. Wenqian Ye, Guangtao Zheng, Aidong Zhang
COCO-Tree: Compositional Hierarchical Concept Trees for Enhanced Reasoning in Vision-Language Models, the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025) (Main conference paper).
Sanchit Sinha, Guangzhi Xiong, and Aidong Zhang,
FedMBridge: Bridgeable Multimodal Federated Learning,International conference on machine learning (ICML2024), Vienna, Austria, July 21-27, 2024 (oral presentation)
Jiayi Chen and Aidong Zhang
Medcalc-bench: Evaluating large language models for medical calculations. NeurIPS 2024 Track Datasets and Benchmarks, 2024.
Nikhil Khandekar, Qiao Jin, Guangzhi Xiong, Soren Dunn, Serina S Applebaum, Zain Anwar, Maame SarfoGyamfi, Conrad W Safranek, Abid A Anwar, Andrew Zhang, Aidan Gilson, Maxwell B Singer, Amisha Dave, Andrew Taylor, Aidong Zhang, Qingyu Chen, and Zhiyong Lu
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
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
Benchmarking Retrieval-Augmented Generation for Medicine, the ACL Findings, 2024.
Guangzhi Xiong, Qiao Jin, Zhiyong Lu, 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
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
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
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
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
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
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
NIH Project
Continually Adaptive Machine Learning Platform for Personalized Biomedical Literature Curation and Exploration
NIH Project
Fairness and Robust Interpretability of Prediction Approaches for Aging and Alzheimer’s Disease
NSF Project
SCH: Personal Determinants of Health Enhanced Machine Learning Models for Early Prediction of Alzheimer’s Disease and Related Dementias
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.