Quanling Deng


Research interests#

  • Mathematical modeling and simulation: fluid flow through poroelastic media, ocean and atmosphere dynamics, sea ice floe dynamics.

  • Scientific computing and numerical analysis: parallel computing, preconditioners, post-processing, PDE numerical solvers such as FDM, FVM, FEM, IGA, DG, HHO, Runge–Kutta methods, and generalized-alpha methods, operator splitting schemes, dispersion and spectral analysis, a priori and a posteriori error analysis.

  • Uncertainty quantification and data assimilation: stochastic models, Kalman filters, Ornstein-Uhlenbeck process.

  • Artificial intelligence and machine learning: particle swarm optimization, physics-informed neural networks, supervised learning.


Quanling joined ANU School of Computing in February 2022. He was born in Hunan, China and moved to the USA to study mathematics in August 2011. He graduated with a Ph.D. in computational mathematics with a topic on finite element analysis at the University of Wyoming in May 2016. He then joined Curtin University in Australia as a research associate and mainly contributed to the development of isogeometric analysis. He was a short-term visiting scholar at INRIA Paris, AGH University of Science and Technology in Poland, École des Ponts ParisTech (ENPC), USTC, and others. In March 2020, he joined the Department of Mathematics at the University of Wisconsin-Madison as a Van Vleck visiting assistant professor and worked on modelling and prediction of Arctic sea-ice dynamics.

Available Student Projects#

See here

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