Publications
Publications
* Indicates co-first authors. ✉ indicates Y.He as a (one of) corresponding author(s).
H Jiang, K. Sankaran, and Y. He✉. Joint Adaptive Penalty for Unbalanced Mediation Pathways. [Preprint] [Codes]
C. Chen, Y. He, H. Wang, G. Xu, and P. Song. Quantile Mediation Analytics. [Preprint]
Y. Tian, J. Sun, and Y. He✉. Bridging Theory and Practice: Statistical Inference for Latent Space Models of Networks. [Preprint]
R. Pan, Y.He✉, and J. Park. Boosting multi-view association testing via devariation. [Preprint] [Codes]
(An earlier version of this paper received student paper award (runner-up), ASA Statistics in Imaging section 2025.)
X. Liao, Y. He, D. Bolt, J. Soland, C. Conner, E. Solari (2026). Approximating Multidimensionality with Asymmetric Unidimensional IRT Models.
British Journal of Mathematical and Statistical Psychology. [DOI]
D. Veitch, Y. He✉, and J. Park (2026). Rank-adaptive covariance testing with applications to genomics and neuroimaging.
Biometrics. [DOI] [Preprint] [Codes]
(An earlier version of this paper received 2024 ENAR Distinguished Student Paper Award.)
Y. Tian, J. Sun, and Y. He✉ (2026). Efficient Analysis of Latent Spaces in Heterogeneous Networks.
Journal of the American Statistical Association. [DOI] [Preprint] [Codes]
Y. He✉ (2026). Contribution to the Discussion of "Statistical exploration of the Manifold Hypothesis" by Whiteley et al. in the Journal of the Royal Statistical Society Series B. [DOI]
Y. He*, J. Sun*, Y. Tian*, Z. Ying, and Y. Feng (2025). Semiparametric Modeling and Analysis for Longitudinal Network Data.
Annals of Statistics. [DOI] [Arxiv] [Codes]
Y. He✉ (2024) Extended Asymptotic Identifiability of Nonparametric Item Response Models.
Psychometrika. [DOI]
Y. He, P.X.K. Song, and G. Xu (2024). Adaptive Bootstrap Tests for Composite Null Hypotheses in the Mediation Pathway Analysis.
Journal of the Royal Statistical Society Series B. [DOI] [Codes] [Package]
Y. He, Y. Gu, and Z. Ying (2023) Discussion of ”Vintage factor analysis with Varimax performs statistical inference” by Karl Rohe and Muzhe Zeng in the The Journal of the Royal Statistical Society Series B. [DOI]
Y. Deng*, Y. He*, G. Xu, and W. Pan (2022). Speeding Up Monte Carlo Simulations for the Adaptive Sum of Powered Score Test with Importance Sampling. (* Co-first author)
Biometrics, 78(1), 261-273. [DOI]
Y. He, G. Xu, C. Wu, and W. Pan (2021). Asymptotically Independent U-Statistics in High-Dimensional Testing.
Annals of Statistics, 49(1),154-181. [DOI] [Codes]
(An earlier version of this paper received JSM Travel Award, Biometrics Section, American Statistical Association.)
Y. He, B. Meng, Z. Zeng, and G. Xu (2021). On the Phase Transition of Wilks' Phenomenon.
Biometrika, 108(3),741-748. [DOI]
Y. He, T. Jiang, J. Wen, and G. Xu (2021). Likelihood Ratio Test in Multivariate Linear Regression: from Low to High Dimension.
Statistica Sinica, 31,1215-1238. [DOI]
Y. He, Z. Wang, and G. Xu (2021). A Note on the Likelihood Ratio Test in High-Dimensional Exploratory Factor Analysis.
Psychometrika, 86, 442-46. [DOI]
Y. He and G. Xu (2018). Estimating Tail Probabilities of the Ratio of the Largest Eigenvalue to the Trace of a Wishart Matrix.
Journal of Multivariate Analysis, 166, 320-334. [DOI]
I. Zhang, Y. Fu, M. Liang, and Y. He (2026). When Visuals Come First: Aligning Pre-Instruction and Embodied Pedagogies to Support Learning of Statistical Models.
ISLS 2026 (International Society of the Learning Sciences). Accepted as long paper.
I. Zhang, R. Gao, and Y. He (2025). Mechanisms of Embodied Learning for Learners with Different Prior Knowledge. CogSci 2025. [Preprint]
Poster presentation with full paper publication (Acceptance rate: 56.6%).