School of Mathematics & Statistics

Dr Archer Gong Zhang

Lecturer in Statistics and Data Analytics (Statistics)

email: Archer.Zhang@glasgow.ac.uk
pronouns: He/him/his

Import to contacts

https://orcid.org/0000-0001-9943-3743

Biography

Prior to my role at the University of Glasgow, I was a Departmental Postdoctoral Fellow in the Department of Statistical Sciences at the University of Toronto, where I worked with Dr. Nancy Reid and Dr. Qiang Sun. I got my PhD from the Department of Statistics at the University of British Columbia, under the supervision of Dr. Jiahua Chen.

My personal webpage: https://gozhang.github.io/.

Research interests

I am broadly interested in the theoretical and methodological aspects of Statistics. My current research centres on problems related to data integration and distribution shift. In particular, I study how to make efficient inferences using data collected from multiple sources, where the underlying populations are interconnected and share a common latent structure. A substantial part of my work focuses on inference under a semiparametric model known as the Density Ratio Model, which is closely related to biased sampling, exponential tilting, and proportional likelihood ratio models. I also work on nonparametric methods such as Empirical Likelihood.

Beyond these areas, I have a strong interest in causal inference and in the statistical aspects of machine learning, with a particular focus on transfer learning and related challenges involving distributional shift.

Research groups

Publications

List by: Type | Date

Jump to: 2026 | 2025 | 2024 | 2022 | 2021

Number of items: 6.

2026

Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743 (2026) Archer Gong Zhang's contribution to the discussion of ‘Regression by composition’ by Farewell et al. Journal of the Royal Statistical Society, Series B, (doi: 10.1093/jrsssb/qkag094) (In Press)

2025

Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743 and McVittie, James Hugh (2025) Density ratio model for multiple types of survival data with empirical likelihood. arXiv, (doi: 10.48550/arXiv.2511.09398)

Sun, Qiang, Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743, Liu, Chenyu and Tan, Kean Ming (2025) Resistant convex clustering: how does the fusion penalty enhance resistance? Electronic Journal of Statistics, 19(1), pp. 1199-1230. (doi: 10.1214/25-EJS2359)

2024

Zhang, Qiong, Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743 and Chen, Jiahua (2024) Gaussian mixture reduction with composite transportation divergence. IEEE Transactions on Information Theory, 70(7), pp. 5191-5212. (doi: 10.1109/TIT.2023.3323346)

2022

Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743 and Chen, Jiahua (2022) Density ratio model with data-adaptive basis function. Journal of Multivariate Analysis, 191, 105043. (doi: 10.1016/j.jmva.2022.105043)

2021

Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743, Zhu, Guangyu and Chen, Jiahua (2021) Empirical likelihood ratio test on quantiles under a density ratio model. Electronic Journal of Statistics, 15(2), pp. 6191-6227. (doi: 10.1214/21-EJS1943)

This list was generated on Fri Jul 17 09:14:05 2026 BST.

Jump to: Articles

Number of items: 6.

Articles

Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743 (2026) Archer Gong Zhang's contribution to the discussion of ‘Regression by composition’ by Farewell et al. Journal of the Royal Statistical Society, Series B, (doi: 10.1093/jrsssb/qkag094) (In Press)

Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743 and McVittie, James Hugh (2025) Density ratio model for multiple types of survival data with empirical likelihood. arXiv, (doi: 10.48550/arXiv.2511.09398)

Sun, Qiang, Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743, Liu, Chenyu and Tan, Kean Ming (2025) Resistant convex clustering: how does the fusion penalty enhance resistance? Electronic Journal of Statistics, 19(1), pp. 1199-1230. (doi: 10.1214/25-EJS2359)

Zhang, Qiong, Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743 and Chen, Jiahua (2024) Gaussian mixture reduction with composite transportation divergence. IEEE Transactions on Information Theory, 70(7), pp. 5191-5212. (doi: 10.1109/TIT.2023.3323346)

Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743 and Chen, Jiahua (2022) Density ratio model with data-adaptive basis function. Journal of Multivariate Analysis, 191, 105043. (doi: 10.1016/j.jmva.2022.105043)

Zhang, Archer Gong ORCID: https://orcid.org/0000-0001-9943-3743, Zhu, Guangyu and Chen, Jiahua (2021) Empirical likelihood ratio test on quantiles under a density ratio model. Electronic Journal of Statistics, 15(2), pp. 6191-6227. (doi: 10.1214/21-EJS1943)

This list was generated on Fri Jul 17 09:14:05 2026 BST.

Prior publications

Article

Archer Gong Zhang, Nancy Reid, Qiang Sun (2024) A Semiparametric Approach to Causal Inference Archer Gong Zhang.

Archer Gong Zhang, Jiahua Chen (2023) Optimal Estimation under a Semiparametric Density Ratio Model Archer Gong Zhang.

Thesis

Archer Gong Zhang (2022) Semiparametric inferences under a density ratio model University of British Columbia Archer Gong Zhang. (doi: 10.14288/1.0407289)

Archer Zhang