Research

Selected refereed journal papers:        * Corresponding author 

1. Min, Y., *Peng, L. and *Zou, C. (2026). Enhanced localized conformal prediction with imperfect auxiliary information, Journal of the American Statistical Association, doi.org/10.1080/01621459.2026.2687844.

2. Huang, B., Cheng, G., Liu, Y. and *Peng, L. (2026). Kernel Variable Importance Measure with Applications, Journal of Computational and Graphical Statistics, doi.org/10.1080/10618600.2026.2654770.

3. Huang, W., Li, S. and Peng, L. (2025). Estimation and Inference for Extreme Continuous Treatment Effects, Journal of Business & Economic Statistics, https://doi.org/10.1080/07350015.2024.2430293.

4. Cheng, G., Peng, L. and Zou, C. (2025+). Statistical Inference for Ultrahigh Dimensional Location Parameter Based on Spatial  Median, Statistica Sinica, accepted, https://doi.org/10.5705/ss.202023.0242.

5. Cheng, G., Lin, R. and Peng, L. (2024). High-dimensional Multivariate Analysis of Variance via Geometric Median and Bootstrapping, Biometrics, 80(3). https://doi.org/10.1093/biomtc/ujae088

6. Li, S., *Peng, L. and Song, X. (2023). Simultaneous Confidence Bands for Conditional Value-at-Risk and Expected Shortfall, Econometric Theory, 39(5), 1009-1043. doi.org/10.1017/S0266466622000275

7. Peng, L., Wang, G. and Zou, C. (2023). Measuring, Testing and Identifying Heterogeneity of Large Parallel Datasets, Statistica Sinica, 33, 2787-2808. doi:10.5705/ss.202021.0285. 

8. **Wang, Z., **Peng, L. and Kim, J. K. (2022). Bootstrap Inference for the Finite Population Total Under Complex Sampling Designs, Journal of the Royal Statistical Society: Series B, 84(4), 1150-1174. doi.org/10.1111/rssb.12506. (** Co-first authors)

9. Chen, S. X. and Peng, L. (2021). Distributed Statistical Inference for Massive Data, Ann. Statist., 49(5), 2851-2869.

10. Zou, C., Peng, L., Feng, L. and Wang, Z. (2014). Multivariate Signs-based High-Dimensional Tests for Sphericity, Biometrika, 101(1), 229-236.

Selected refereed conference papers:

1. Min, Y., *Peng, L. and *Zou, C. (2026). Stable Localized Conformal Prediction via Transduction, ICML.

2. Wang, X., Huo, Y., *Peng, L. and *Zou, C. (2026). Learning U-Statistics with Active Inference, ICML.

3. Hu, G., Menendez, P., Liu, F., Gong, M., Wang, G. and *Peng, L. (2026). FedReLa: Imbalanced Federated Learning via Re-Labeling, ICML.

4. Tian, X., Zhou, Z., Peng, L. and Liu, F. (2026). LOTTERY: Learning from Reference-Only Samples in Two-Sample Testing under Size Asymmetry, ICML.

5. Zhou, Z., Peng, L., Tian, X., Gong, M. and Liu, F. (2026). Do You Want to Know if Two Distributions Are Close to Each Other?Testing the Closeness With Statistical Significance, ICML.

6. Min, Y., Zhang, C., *Peng, L. and *Zou, C. (2025). Personalized Federated Conformal Prediction with Localization, NeurIPS.

7. Chen, B., Zhou, C., *Peng, L. and *Wang, Z. (2025). Balanced Active Inference, NeurIPS.

8. Zhou, Z., Peng, L., Tian, X. and Liu, F. (2025). Anchor-based Maximum Discrepancy for Relative Similarity Testing, NeurIPS.

9. Hu, G., Liu, F., Gong, M, Wang, G. and *Peng, L. (2025). Learning Imbalanced Data with Beneficial Label Noise, ICML.

10. Wang, X., Huo, Y., *Peng, L. and *Zou, C. (2024). Conformalized multiple testing after data-dependent selection, NeurIPS.