Zengyan Fan

Dr Fan Zengyan

Deputy Head, Mathematics Programme and Head, Minor in Data Science Programme

School of Science and Technology

Tel: +65 6248 9639

Email: enlmYW5Ac3Vzcy5lZHUuc2c=

Educational Qualifications

PhD (Statistics), Nanyang Technological University, Singapore

Academic and Professional Experience

2020 - Present
Lecturer, School of Science & Technology, SUSS

2017 - 2019
Research Fellow, Department of Statistics and Applied Probability, NUS

Y. Wang, H. Lin, Z. Fan, and H. Lian. (2024)
Locally adaptive sparse additive quantile regression model with TV penalty. Journal of Statistical Planning and Inference, 106144

Z. Yao, Y. Xia and Z. Fan. (2023)
Random Fixed Boundary Flows. Journal of the American Statistical Association, (just-accepted), 1-22.

S. S. Salamat, F. Liu, Z. Fan and W. Zhang. (2023)
It Is About Weather: Explainable Machine Learning for Traffic Accident Understanding, IEEE Conference on Systems, Man, and Cybernetics (SMC). In Press. IEEE. Hawaii, USA.

H. Lian, J. Liu and Z. Fan. (2021)
Distributed learning for sketched kernel regression. Neural Networks, 143, 368-376.

Y. Tian, H. Lin, H. Lian and Z. Fan. (2021)
Additive functional regression in reproducing kernel Hilbert spaces under smoothness condition. Metrika, 84, 429-442.

S. Lv, Z. Fan, H. Lian, T. Suzuki and K. Fukumizu. (2020)
A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model. Computational Statistics & Data Analysis, 152, 107039.

Z. Yao, Z. Fan, M. Hayashi and W. F. Eddy. (2020)

Quantifying time-varying sources in Magnetoencephalography – a discrete approach. Annals of Applied Statistics. 14 (3) 1379 - 1408.

H. Lian, Z. Fan. (2018)
Divide-and-conquer for debiased l1-norm support vector machine in ultra-high dimensions. The Journal of Machine Learning Research. 18 (1), 6691-6716.

Z. Fan and H. Lian. (2018)
Quantile regression for additive coefficient models in high dimensions. Journal of Multivariate Analysis. 164, 54-64.

Z. Fan and H. Lian. (2017)
Interquantile shrinkage in additive models. Journal of Nonparametric Statistics. 29 (3), 561-576.

H. Lian and Z. Fan. (2016)
Minimax convergence rates for kernel CCA. Journal of Multivariate Analysis. 150, 183-190.

H. Lian, J. Meng and Z. Fan. (2015)
Simultaneous estimation of linear conditional quantiles with penalized splines. Journal of Multivariate Analysis. 141, 1-21.

H. Lian and Z. Fan. (2015)
Estimation of a sparse and spiked covariance matrix. Journal of Nonparametric Statistics. 27, 241-252.

L. Zhao and Z. Fan. (2013)
The number of small amplitude limit cycles in arbitrary polynomial systems. Journal of Mathematical Analysis and Applications. 407 (2), 237-249.

2023 - Present
Reviewer for the Journal of the American Statistical Association

2020 - Present
Reviewer for Journal of Machine Learning Research

2019 - Present
Reviewer for International Journal of Machine Learning and Cybernetics

  • High dimensional statistical problems
  • Functional data analysis
  • Non-Euclidean data analysis
  • Network data analysis
  • GTP: A R version of the GTP algorithm (proposed by Dr. Megan Owens) to compute geodesic distance and paths between phylogenetic trees in polynomial time. The R package is available on GitHub through https://github.com/FloraZFan/GTP

  • RFBF: A R code to analyze variations locally and globally for complex data on non-linear Riemannian manifolds. The R package is available on GitHub through https://github.com/FloraZFan/Random-Fixed-Boundary-Flows
    • Z. Yao, Y. Xia and Z. Fan. (2023). Random Fixed Boundary Flows. Journal of the American Statistical Association, (just-accepted), 1-22.
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