Career • 2026.01- present, Associate Professor, ShanghaiTech University • 2022.05- 2026.01, Assistant Professor, University of Birmingham • 2020.11- 2022.01, Assistant Professor, ShanghaiTech University • 2018.09-2020.08, Postdoctoral Associate, Virginia Tech
Education • 2013.09-2018.09, Ph.D in Mathematics, University of Massachusetts Dartmouth • 2009.09-2013.09, B.S. in Mathematics, University of Science and Technology of China
Research Interest My research interests include inverse problem with its application in imaging processing, model order reduction, uncertainty quantification, deep learning and data science.
Publications [1] J. Zhang, L. Li, Q. Hu, J. Zhang, Y. Wu, L. Gu, J. Li, F. Li, X. Zhu*, J. Jiang*, W. Ren*, High-Fidelity Solution Decomposition Fluorescence Tomography in the Presence of Background Interference, Laser & Photonics Reviews, 2025 (Selected as Journal Cover).
[2] M. S. Landman, J. Chung*, J. Jiang, S. Miller, A. Saibaba, A Joint Reconstruction and Model Selection Approach for Large Scale Inverse Modeling, Geoscientific Model Development, 2024.
[3] S. Shen, L. Li, S. Gao, Y. Wang, L. Gu, S. Li, X. Zhu, J. Jiang*, J. Yu*, W. Ren*, High Resolution Diffuse Optical Tomography via Neural Fields, IEEE Transactions on Computational Imaging, 2024.
[4] M. Landman*, J. Chung*, J. Zhang, W. Ren, Augmented Flexible Krylov Subspace methods with applications to Bayesian inverse problems, Linear Algebra and its Applications, 2024.
[5] Y. Wu, Y. Hu, L. Li, J. Jiang, X. Zhu*, W. Ren*, Simultaneous reconstruction of 3D fluorescence distribution and object surface using structured light illumination and dual-camera detection, Optics Express 32 (9), 15760-15773, 2024.
[6] J. Zhang, Z. Wang, T. Cao, G. Cao*, W. Ren*, J. Jiang*, Fast, accurate and robust sparse-view CT reconstruction via residual-guided Golub-Kahan iterative reconstruction technique (RGIRT), Physics in Medicine & Biology 69 (10), 105010, 2024.
[7] J. Chung, J. Jiang*, SM. Miller, AK. Saibaba, Hybrid Projection Methods for Solution Decomposition in Large-scale Bayesian Inverse Problems, SIAM Journal on Scientific Computing 46 (2), S97-S119, 2024.
[8] Y. Wu, S. Gao, L. Li, J. Zhang, Q. Hu, X. Lou, X. Zhu, J. Jiang*, W. Ren*, Multifunctional optical tomography system with high-fidelity surface extraction based on a single programmable scanner and unified pinhole modeling, IEEE Transactions on Biomedical Engineering, 2023.
[9] R. Guo, Y. Li, J. Jiang*, Learn An Index Operator by CNN for Solving Diffusive Optical Tomography: A Deep Direct Sampling Method, Journal of Scientific Computing, 95 (31), 2023.
[10] Z. Guo, X. Ren, J. Jiang, H. Liu, Y. Huo, X. Zhao, K. N. TuAkIl, Y. Liu, The Design of Eutectic High Entropy Solder by Machine Learning, Patent, No. ZL202110560280.1, 2022.
[11] E. Qian, J. Tabeart, C. Beattie, S. Gugercin, J. Jiang, P. Kramer, Akil Narayan, Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference, Journal of Scientific Computing, 91(1), pp. 1-30, 2022.
[12] J. Lin, C. Jiang, J. Jiang, Conjugate Gradient Persymmetric Adaptive Matched Filter, Digital Signal Processing, 123, p. 103395, 2022.
[13] J. Jiang*, Fatoumata Sanogo, Carmeliza Navasca, Low-CP-rank Tensor Completion via Practical Regularization, Journal of Scientific Computing, 91(1), pp. 1-20, 2022.
[14] R. Guo and J. Jiang*, Construct Deep Neural Networks Based on Direct Sampling Methods for Solving Electrical Impedance Tomography, SIAM Journal on Scientific Computing 43 (3), B678-B711, 2021.
[15] J. Chung, E. Sturler, J. Jiang*, Hybrid Projection Methods with Recycling for Inverse Problems, SIAM Journal on Scientific Computing, S146-S172, 2021.
[16] T. Cho, J. Chung, J. Jiang*, Hybrid Projection Methods for Large-scale Inverse Problems with Mixed Gaussian Priors, Inverse Problems, 37(4), 2021, pp. 044002.
[17] J. Jiang, Y. Chen, Multi-level Adaptive Greedy Algorithms for the Reduced Basis Method, International Journal for Numerical Methods in Engineering, 121 (23), 2020, pp. 5426-5445.
[18] Y. Chen, J. Jiang and A. Narayan, Robust Residual-based and Residual-free Greedy Algorithms for Reduced Basis Methods, Computers & Mathematics with Applications, 77(7), 2019, pp. 1963-1979.
[19] B. Dong, J. Jiang and Y. Chen, Optimally Convergent Hybridizable Discontinuous Galerkin Method for Fifth-order Korteweg-de Vries Type Equations, Mathematical Modeling and Numerical Analysis (ESAIM: M2AN), 52(6), 2019, pp. 2283-2306.
[20] J. Jiang, Y. Chen and A. Narayan, Offline-enhanced Reduced Basis Method through Adaptive Construction of the Surrogate Training Set, Journal of Scientific Computing, 73(2-3), 2017, pp. 853–875.
[21] J. Jiang, Y. Chen and A. Narayan, A Goal-oriented Reduced Basis Methods-accelerated Generalized Polynomial Chaos Algorithm, SIAM/ASA Journal on Uncertainty Quantification, 4(1), 2016, pp. 1398-1420. | Email: jiangjh@shanghaitech.edu.cn Office: S314, School of Creativity & Arts |