Link to DBLP and Google Scholar. You can find the code for reproducing our empirical work in the following GitHub. Acknowledgement: Our research has been generously supported by funds from the National Science Foundation and from JP Morgan Chase.

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1. Efficient Estimation of Kernel Surrogate Models for Task Attribution
   Z. Zhang, M. Duan, and H. R. Zhang
   International Conference on Learning Representations (ICLR), 2026
   openreview

2. One-Sided Matrix Completion from Ultra-Sparse Samples
   H. R. Zhang, Z. Zhang, H. L. Nguyen, and G. Lan
   Transactions on Machine Learning Research (TMLR), 2026. Featured Certification
   openreview. Also presented at NeurIPS’25 Workshop on Optimization and Machine Learning

3. Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning
   D. Li, Z. Zhang, M. Duan, E. Dobriban, and H. R. Zhang
   To appear in KDD, 2026

4. Learning Multimodal Embeddings for Traffic Accident Prediction and Causal Estimation
   Z. Zhang, M. Duan, H. N. Koutsopoulos, and H. R. Zhang
   To appear in KDD, 2026 (Datasets)
   arXiv preprint
   

5. Scalable Multi-Objective and Meta Reinforcement Learning via Gradient Estimation
   Z. Zhang, M. Duan, Y. Ye, and H. R. Zhang
   To appear in AAAI, 2026
   arXiv preprint
   

6. Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation
   Z. Zhang*, Z. Zhang*, D. Li, L. Wang, J. Dy, and H. R. Zhang
   Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025
   

7. Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers
   F. Yang*, H. R. Zhang*, S. Wu, C. Ré, and W. Su
   Journal of Machine Learning Research (JMLR), 2025
   

8. Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets
   D. Li, Z. Zhang, L. Wang, and H. R. Zhang
   Association for Computational Linguistics (ACL), 2025
   

9. Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach
   H. R. Zhang, D. Li, and H. Ju
   Transactions on Machine Learning Research (TMLR), 2024
   

10. Scalable Fine-tuning From Multiple Data Sources: A First-order Approximation Approach
    D. Li, Z. Zhang, L. Wang, and H. R. Zhang
    Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP), 2024
    

11. Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity
    D. Li, A. Sharma, and H. R. Zhang
    ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2024
    

12. Learning Tree-Structured Composition of Data Augmentation
    D. Li, K. Chen, P. Radivojac, and H. R. Zhang
    Transactions on Machine Learning Research (TMLR), 2024
    

13. Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis
    A. Nippani, D. Li, H. Ju, H. N. Koutsopoulos, and H. R. Zhang
    Neural Information Processing Systems (NeurIPS Datasets Track), 2023
    

14. Improved Group Robustness via Classifier Retraining on Independent Splits
    T. H. Nguyen, H. R. Zhang, and H. L. Nguyen
    Transactions on Machine Learning Research (TMLR), 2023
    

15. Boosting Multitask Learning on Graphs through Higher-Order Task Affinities
    D. Li, H. Ju, A. Sharma, and H. R. Zhang
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
    

16. Identification of Negative Transfers in Multitask Learning Using Surrogate Models
    D. Li, H. L. Nguyen, and H. R. Zhang
    Transactions on Machine Learning Research (TMLR), 2023. Featured Certification
    

17. Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
    H. Ju, D. Li, A. Sharma, and H. R. Zhang
    Artificial Intelligence and Statistics (AISTATS), 2023
    

18. Optimal Intervention on Weighted Networks via Edge Centrality
    D. Li, T. Eliassi-Rad, and H. R. Zhang
    SIAM International Conference on Data Mining (SDM), 2023
    

19. Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees
    H. Ju, D. Li, and H. R. Zhang
    International Conference on Machine Learning (ICML), 2022
    

20. Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations
    M. Zhang, N. Sohoni, H. R. Zhang, C. Finn, and C. Ré
    International Conference on Machine Learning (ICML), 2022. Long presentation
    

21. Incentive Ratio: A Game Theoretical Analysis of Market Equilibria
    N. Chen, X. Deng, B. Tang, H. R. Zhang, and J. Zhang
    Information and Computation, 2022
    

22. Improved Regularization and Robustness for Fine-tuning in Neural Networks
    D. Li and H. R. Zhang
    Neural Information Processing Systems (NeurIPS), 2021
    

23. Observational Supervision for Medical Image Classification using Gaze Data
    K. Saab, S. Hooper, N. Sohoni, J. Parmar, B. Pogatchnik, S. Wu, J. Dunnmon, H. R. Zhang, D. Rubin, and C. Ré
    Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2021
    

24. On the Generalization Effects of Linear Transformations in Data Augmentation
    S. Wu*, H. R. Zhang*, G. Valiant, and C. Ré
    International Conference on Machine Learning (ICML), 2020
    

25. Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK
    Y. Li*, T. Ma*, and H. R. Zhang*
    Annual Conference on Learning Theory (COLT), 2020
    

26. Understanding and Improving Information Transfer in Multi-Task Learning
    S. Wu*, H. R. Zhang*, and C. Ré
    International Conference on Learning Representations (ICLR), 2020
    

27. Algorithms and Generalization for Large-scale Matrices and Tensors
    Thesis Ph.D
    Stanford University, 2019
    

28. Pruning based Distance Sketches with Provable Guarantees on Random Graphs
    H. Zhang, H. Yu, and A. Goel
    The Web Conference (WWW) 2019. Oral presentation
    

29. Recovery Guarantees for Quadratic Tensors with Sparse Observations
    H. Zhang, V. Sharan, M. Charikar, and Y. Liang
    Artificial Intelligence and Statistics (AISTATS), 2019
    

30. Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations
    Y. Li*, T. Ma*, and H. Zhang*
    Conference on Learning Theory (COLT) 2018. Best Paper Award
    

31. Approximate Personalized PageRank on Dynamic Graphs
    H. Zhang, P. Lofgren, and A. Goel
    KDD 2016. Oral presentation. [code]
    

32. Incentives for Strategic Behavior in Fisher Market Games
    N. Chen*, X. Deng*, B. Tang*, and H. Zhang*
    AAAI, 2016
    

33. A Note on Modeling Retweet Cascades on Twitter
    A. Goel*, K. Munagala*, A. Sharma*, and H. Zhang*
    Workshop on Algorithms and Models for the Web Graph (WAW), 2015
    

34. Connectivity in Random Forests and Credit Networks
    A. Goel*, S. Khanna*, S. Raghvendra*, and H. Zhang*
    Symposium on Discrete Algorithms (SODA), 2015
    

35. Computing the Nucleolus of Matching, Cover and Clique Games
    N. Chen*, P. Lu*, and H. Zhang*
    AAAI, 2012. Oral presentation
    

36. Incentive Ratios of Fisher Markets
    N. Chen*, X. Deng*, H. Zhang*, and J. Zhang*
    International Colloquium on Automata, Languages, and Programming (ICALP), 2012
    

37. Fixed-Parameter Tractability of almost CSP Problem with Decisive Relations
    C. Zhang and H. Zhang
    FAW-AAIM, 2012
    

38. On Strategy-proof Allocation without Payments or Priors
    L. Han*, C. Su*, L. Tang*, and H. Zhang*
    Conference on Web and Internet Economics (WINE), 2011