20002020

Research output per year

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Personal profile

Research interests

Computational Biology, Computational Statistics, Multi-scale modelling of complex networks

Supervision interests

Mathematical modelling of genetic network and cell signalling pathway, mathematical modelling of financial and social networks; Statistical inference of complex networks;

Biography

TianhaiTian received his PhD in Computational Mathematics in 2001 from the University of Queensland in Australia. He was a Research Fellow at the same University after submitting his PhD thesis. He obtained the Australian Research Fellowship from the Australian Research Council (ARC) in 2006 and then studied computational biology at the Institute for Molecular Bioscience in Queensland. He joined the University of Glasgow in Scotland as a Lord Kelvin Fellow in 2007 and became a Reader in 2009. In 2011 he returned to Australia and now is an Associate Professor and ARC Future Fellow at the School of Mathematical Sciences, Monash University.

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Projects

Research Output

Control-based algorithms for high dimensional online learning

Ning, H., Zhang, J., Feng, T. T., Chu, E. K. W. & Tian, T., Feb 2020, In : Journal of the Franklin Institute. 357, 3, p. 1909-1942 34 p.

Research output: Contribution to journalArticleResearchpeer-review

A clustering-based ensemble approach with improved pigeon-inspired optimization and extreme learning machine for air quality prediction

Jiang, F., He, J. & Tian, T., 2019, In : Applied Soft Computing Journal. 85, p. 1-14 14 p., 105827.

Research output: Contribution to journalArticleResearchpeer-review

Approximate Bayesian Computational Methods for the Inference of Unknown Parameters

Ke, Y. & Tian, T., 14 Mar 2019, 2017 MATRIX Annals. Wood, D. R., de Gier, J., Praeger, C. E. & Tao, T. (eds.). Cham Switzerland: Springer, Vol. 2. p. 515-529 15 p. (MATRIX Book Series; vol. 2).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Open Access
File

Asymptotic-numerical solvers for highly oscillatory second-order differential equations

Liu, Z., Tian, T. & Tian, H., 1 Mar 2019, In : Applied Numerical Mathematics. 137, p. 184-202 19 p.

Research output: Contribution to journalArticleResearchpeer-review

Mathematical modeling and dynamic analysis of anti-tumor immune response

Pang, L., Liu, S., Zhang, X. & Tian, T., 1 Jan 2019, (Accepted/In press) In : Journal of Applied Mathematics and Computing.

Research output: Contribution to journalArticleResearchpeer-review

Press / Media