20002019
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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 2007 2017

Research Output 2000 2019

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

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

Mathematical modelling the pathway of genomic instability in lung cancer

Li, L., Zhang, X., Tian, T. & Pang, L., 1 Dec 2019, In : Scientific Reports. 9, 1, 9 p., 14136.

Research output: Contribution to journalArticleResearchpeer-review

Open Access

Online Identification of Nonlinear Stochastic Spatiotemporal System with Multiplicative Noise by Robust Optimal Control-Based Kernel Learning Method

Ning, H., Qing, G., Tian, T. & Jing, X., 1 Feb 2019, In : IEEE Transactions on Neural Networks and Learning Systems. 30, 2, p. 389-404 16 p., 8399841.

Research output: Contribution to journalArticleResearchpeer-review

Press / Media