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Personal profile

Research interests

Conduct research on the following main projects:

• Tensor decompositions (TDs) and novel applications:

- Deal with most challenging problems in tensor decompositions, e.g., high computational cost of algorithms, the second-order optimization method, a measure of performance of algorithms, massive tensor decomposition, tensor deflation.

- Develop robust algorithms with low computational costs for various low-rank tensor decompositions of large-scale data, including the Candecomp/Parafac, Tucker tensor decompositions, low-rank tensor deconvolution, tensor diagonalization, Kronecker tensor decomposition, tensor deflation, feature extraction for multiway data.

- We contributed state-of-the-art algorithms to the tensor analysis, especially for the Candecomp/Parafac tensor decomposition. Source codes of the developed algorithms are provided in the package TENSORBOX.

• Blind Sources Separation. We developed the algorithms for blind source separation based on independent component analysis, nonnegative matrix factorization and tensor network decomposition. Our methods consist of two steps: tensorization of the mixture signals to yield tensors, low-rank tensor decomposition to retrieve the hidden sources.

• Brain Computer Interface (BCI): we applied tensor decomposition to extract relevant features for EEG signals in BCI system.

• Nonlinear system identification based on multivariate polynomial regression, Volterra-type models, in which parameters are represented in the Tensor network format. Our models can be applied to regression, discriminant analysis, support vector machines, deep learning, data fusion, and feature combination.

• Other research:

- Early detection of Alzheimer disease

- Deconvolution of large-scale Calcium imaging data

- Coding of faces by components with complexity constraints

Academic Reputation and Societal Impact

The reviewer of journals Linear Algebra and Its Applications, SIAM Journal on Matrix Analysis and Applications, SIAM Journal on Mathematics of Data Science, IEEE Transaction on Signal Processing, IEEE Transaction on Neural Network and Learning Systems, Chemometrics and Intelligent Laboratory Systems, Neural Computing and Applications, and many international conferences, ICASSP 2019, ICASSP 2020, ATC 2019, GlobalSIP’ 2019, EUSIPCO 2019, ICIP 2019.

Developed and released a new version of the Tensorbox toolbox in 2019. The toolbox comprises state-of-the-art algorithms to the various tensor decompositions and tensor network.


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