Back to
Dr Ziyang Lyu

Dr Ziyang Lyu

Senior Lecturer
Science
School of Mathematics & Statistics

Dr. Ziyang Lyu is a Senior Lecturer (tenured) and an ARC DECRA Fellow in Statistics at the School of Mathematics and Statistics, University of New South Wales. He received his Ph.D. in Statistics from the Australian National University in 2020 and subsequently held postdoctoral appointments at The University of Queensland (2020–2021) and UNSW (2021–2024). He joined the UNSW faculty as a Lecturer in January 2025 and was promoted to Senior Lecturer in July 2026.

 

Research interests:

  • Theoretical statistics:  Asymptotic theory, longitudinal data analysis, mixed models with complex covariance structures (particularly crossed random-effects models), and finite mixture models.
  • Applied statistics:  Semi-supervised learning, pattern recognition, and statistical modelling for battery lifetime prediction and intelligent battery management system (iBMS).

His research has been published in leading statistical journals, including Annals of Statistics, Journal of the American Statistical Association, Biometrika, and Statistica Sinica.

 

Prospective students: Dr. Lyu welcomes applications from self-motivated students with a strong background in mathematics and statistics. Interested applicants are encouraged to email their CV, academic transcripts, and any research papers they have authored (or a research proposal/research statement). Scholarships are available for qualified Ph.D. students.

 

 
E-mail
ziyang.lyu@unsw.edu.au
Location
UNSW Sydney NSW 2052, AUSTRALIA
  • Journal articles | 2026
    Hu H; Huang X; Liang C; Lyu Z; Su L; Li K; Qin Z; Mo H; Zhang X; Zou C; Tao S, 2026, 'Second-level heterogeneous retired battery type identification using pulse-test-enabled federated learning with output-level privacy preservation', Etransportation, 29, http://dx.doi.org/10.1016/j.etran.2026.100607
    Journal articles | 2026
    Jinyang L; Lyu Z, 2026, 'Semi-Supervised Mixture Models under the Concept of Missing at Radom with Margin Confidence and Aranda Ordaz Function', arXiv, https://arxiv.org/abs/2601.14631
    Journal articles | 2026
    Liang C; Tao S; Shi H; Lyu Z; Ji JC; Dong D; Mo H, 2026, 'Pulse excitation for active battery management systems', npj Clean Energy, 2, http://dx.doi.org/10.1038/s44406-026-00040-w
    Journal articles | 2026
    Liang C; Tao S; Xia C; Huang X; Hu H; Wang R; Dong D; Lyu Z; Zhou G; Mo H, 2026, 'Inline quality grading of commercial lithium-ion battery manufacturing via data-efficient learning and transferable assessment', Energy and Environmental Science, http://dx.doi.org/10.1039/d6ee02209j
    Journal articles | 2026
    Liao J; Lyu Z, 2026, 'Semi-Supervised Mixture Models Under the Concept of Missing at Random with Margin Confidence and Aranda-Ordaz Function', Advanced Intelligent Computing Technology and Applications, http://dx.doi.org/10.1007/978-981-92-3450-9_25
    Journal articles | 2026
    Lyu Z; Sisson SA; Welsh AH, 2026, 'On the inverse of covariance matrices for unbalanced crossed designs', Biometrika, http://dx.doi.org/10.1093/biomet/asag041
    Journal articles | 2026
    Lyu Z, 2026, 'Semi-Supervised Mixture Models under the Concept of Missing at Radom with Margin Confidence and Aranda Ordaz Function', arXiv, https://arxiv.org/abs/2601.14631
    Journal articles | 2025
    Lyu Z; Sisson S; Welsh AH, 2025, 'Asymptotics for EBLUPs within crossed mixed effect models', Submitted to Journal of the American Statistical Association, https://arxiv.org/abs/2502.04723
    Journal articles | 2025
    Lyu Z; Sisson SA; Welsh AH, 2025, 'On the inverse of covariance matrices for unbalanced crossed designs', Submitted to Annals of Statistics, http://dx.doi.org/10.48550/arxiv.2512.09273
    Journal articles | 2025
    Lyu Z; Welsh AH, 2025, 'Small Area Estimation using EBLUPs under the Nested Error Regression Model', Statistica Sinica, 35, pp. 1277 - 1299, http://dx.doi.org/10.5705/ss.202023.0045
    Journal articles | 2024
    Lyu Z; Ahfock D; Thompson R; McLachlan GJ, 2024, 'gmmsslm: Semi-supervised Gaussian mixture modeling with a missing data mechanism in R', Australian and New Zealand Journal of Statistics, http://dx.doi.org/10.1111/anzs.12413
    Journal articles | 2024
    Lyu Z; Sisson S; Welsh AH, 2024, 'Increasing Dimension Asymptotics for Two-Way Crossed Mixed Effect Models', Annals of Statistics, 52, pp. 2956 - 2978, http://dx.doi.org/10.1214/24-AOS2469
    Journal articles | 2023
    Lyu Z; Poynton S; Sisson S, 2023, 'The impact of changes to liquor licensing policy on violent crime in NSW, 2000-2019', Crime and Justice Bulletin, NO.263, https://bocsar.nsw.gov.au/documents/publications/cjb/cjb251-300/CJB263-Report-Liquor-licensing-policy.pdf
    Journal articles | 2023
    Lyu Z, 2023, 'Analysis of estimating the Bayes rule for Gaussian mixture models with a specified missing-data mechanism', Computational Statistics, https://doi.org/10.1007/s00180-023-01447-0
    Journal articles | 2022
    Lyu Z; Welsh AH, 2022, 'Asymptotics for EBLUPs: Nested Error Regression Models', Journal of the American Statistical Association, 117, pp. 2028 - 2042, http://dx.doi.org/10.1080/01621459.2021.1895178
    Journal articles | 2022
    Lyu Z; Welsh AH, 2022, 'Increasing cluster size asymptotics for nested error regression models', Journal of Statistical Planning and Inference, 217, pp. 52 - 68, http://dx.doi.org/10.1016/j.jspi.2021.07.009
    Journal articles | 2018
    Lyu Z; Peng K; Hu C-P, 2018, 'P-Value, Confidence Intervals, and Statistical Inference: A New Dataset of Misinterpretation', FRONTIERS IN PSYCHOLOGY, 9, http://dx.doi.org/10.3389/fpsyg.2018.00868
  • Working Papers | 2024
    Lyu Z; Sisson S; Welsh AH, 2024, Increasing Dimension Asymptotics for Two-Way Crossed Mixed Effect Models, http://dx.doi.org, https://arxiv.org/abs/2401.06446
    Working Papers | 2022
    2022, Small Area Estimation using EBLUPs under the Nested Error Regression Model, http://dx.doi.org10.48550/arXiv.2210.09502
    Working Papers | 2022
    2022, Some Simulation and Empirical Results for Semi-Supervised Learning of the Bayes Rule of Allocation, http://dx.doi.org10.48550/arXiv.2210.13785, https://arxiv.org/abs/2210.13785
  • Preprints | 2026
    Jinyang L; Lyu Z, 2026, Semi-Supervised Mixture Models under the Concept of Missing at Radom with Margin Confidence and Aranda Ordaz Function, https://arxiv.org/abs/2601.14631
    Preprints | 2025
    Lyu Z; Sisson SA; Welsh AH, 2025, On the inverse of covariance matrices for unbalanced crossed designs, http://dx.doi.org/10.48550/arxiv.2512.09273
    Preprints | 2024
    Lyu Z; Sisson SA; Welsh AH, 2024, Increasing dimension asymptotics for two-way crossed mixed effect models, http://dx.doi.org/10.1214/24-AOS2469
    Preprints | 2024
    Lyu Z; Sisson SA; Welsh AH, 2024, Increasing dimension asymptotics for two-way crossed mixed effect models, , http://arxiv.org/abs/2401.06446v2
    Preprints | 2023
    Lyu Z; Ahfock D; Thompson R; McLachlan GJ, 2023, Semi-supervised Gaussian mixture modelling with a missing-data mechanism in R, , http://arxiv.org/abs/2302.13206v3
    Preprints | 2022
    Lyu Z; Ahfock D; McLachlan GJ, 2022, Some Simulation and Empirical Results for Semi-Supervised Learning of the Bayes Rule of Allocation, http://arxiv.org/abs/2210.13785v1
    Preprints | 2022
    Lyu Z; Welsh AH, 2022, Small Area Estimation using EBLUPs under the Nested Error Regression Model, http://arxiv.org/abs/2210.09502v1
    Preprints | 2021
    Lyu Z; Welsh AH, 2021, Increasing Cluster Size Asymptotics for Nested Error Regression Models, http://arxiv.org/abs/2101.08951v1

  1. 2026-2029 Involved (Lead CI) in the project 'Advanced statistical methods for complex longitudinal data ', Australian Research Council Discovery Early Career Researcher Award (DECRA)​​​​​​, 480,678 AUD​
  2. 2026-2027 Involved (Lead CI) in the project 'Scalable Statistical Integrated Technologies for the Second-Life Utilization of Lithium-Ion Batteries', TRaCE Lab to Market fund, Australia, 1,300,000 AUD

My Research Supervision

1. Zhanzhongyu Gao (PhD student)

2. Chen Liang (PhD student)

3. Hao Shi (PhD student)

 

My Teaching

2026:

MATH2871-Data Management for Statistical Analysis (Course Convener)

 

2025:

MATH2871-Data Management for Statistical Analysis (Course Convener)

MATH5846-Introduction to Probability and Stochastic Processes  (Course Convener)

 

2024:

MATH5856- Introduction to Statistics and Statistical Computations (Course Convener)

MATH5806-Applied Regression Analysis(Course Convener)