Dr Jiahua Jiang PhD

Dr Jiahua Jiang

School of Mathematics
Assistant Professor

Contact details

Address
School of Mathematics
Watson Building
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Jiahua Jiang is an Assistant Professor at the School of Mathematics of the University of Birmingham.

Jiahua Jiang's personal webpage

Qualifications

  • PhD in Engineering and Applied Science, University of Massachusetts Dartmouth, US, 2018
  • BS in Applied Mathematics, University of Science and Technology of China, 2013

Biography

Jiahua Jiang received a BS degree in Applied Mathematics from the University of Science and Technology of China in 2013, and a PhD in Engineering and Applied Science from the University of Massachusetts Dartmouth in 2018. After her PhD degree, Jiahua did postdoctoral research at Virginia Tech. She subsequentially worked at ShanghaiTech University (assistant professor, 2020–2021). She joined the University of Birmingham as an assistant professor in 2022.

Postgraduate supervision

I am happy to discuss PhD project supervision with potential candidates; please email me if you are interested.

Research

Research Themes

  • Inverse Problem and Imaging
  • Model Order Reduction
  • Uncertainty Quantification

Publications

Recent publications

Article

Lin, J, Jiang, C, Jiang, J & Kang, J 2022, 'Conjugate gradient persymmetric adaptive matched filter', Digital Signal Processing, vol. 123, 103395. https://doi.org/10.1016/j.dsp.2022.103395

Jiang, J, Sanogo, F & Navasca, C 2022, 'Low-CP-rank tensor completion via practical regularization', Journal of Scientific Computing, vol. 91, no. 1, 18 . https://doi.org/10.1007/s10915-022-01789-9

Qian, E, Tabeart, JM, Beattie, C, Gugercin, S, Jiang, J, Kramer, PR & Narayan, A 2022, 'Model reduction of linear dynamical systems via balancing for Bayesian inference', Journal of Scientific Computing, vol. 91, no. 1, 29 . https://doi.org/10.1007/s10915-022-01798-8

Guo, R & Jiang, J 2021, 'Construct deep neural networks based on direct sampling methods for solving electrical impedance tomography', SIAM Journal on Scientific Computing, vol. 43, no. 3, pp. B678-B711. https://doi.org/10.1137/20M1367350

Cho, T, Chung, J & Jiang, J 2021, 'Hybrid projection methods for large-scale inverse problems with mixed Gaussian priors', Inverse Problems, vol. 37, no. 4, 044002. https://doi.org/10.1088/1361-6420/abd29d

Jiang, J, Chung, J & Sturler, ED 2021, 'Hybrid projection methods with recycling for inverse problems', SIAM Journal on Scientific Computing, vol. 43, no. 5, pp. S146--S172. https://doi.org/10.1137/20M1349515

Jiang, J & Chen, Y 2020, 'Adaptive greedy algorithms based on parameter-domain decomposition and reconstruction for the reduced basis method', International Journal for Numerical Methods in Engineering, vol. 121, no. 23, pp. 5426-5445. https://doi.org/10.1002/nme.6544

Chen, Y, Jiang, J & Narayan, A 2019, 'A robust error estimator and a residual-free error indicator for reduced basis methods', Computers & Mathematics with Applications, vol. 77, no. 7, pp. 1963-1979. https://doi.org/10.1016/j.camwa.2018.11.032

Chen, Y, Dong, B & Jiang, J 2018, 'Optimally convergent hybridizable discontinuous Galerkin method for fifth-order Korteweg-de Vries type equations', ESAIM: M2AN, vol. 52, no. 6, pp. 2283-2306. https://doi.org/10.1051/m2an/2018037

Jiang, J, Chen, Y & Narayan, A 2017, 'Offline-Enhanced Reduced Basis Method Through Adaptive Construction of the Surrogate Training Set', Journal of Scientific Computing, vol. 73, pp. 853-875. https://doi.org/10.1007/s10915-017-0551-3

Jiang, J, Chen, Y & Narayan, A 2016, 'A Goal-Oriented Reduced Basis Methods-Accelerated Generalized Polynomial Chaos Algorithm', SIAM/ASA Journal on Uncertainty Quantification, vol. 4, no. 1, pp. 1398-1420. https://doi.org/10.1137/16M1055736

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