• IC1.54, Stephenson Building, Teesside University

20192019
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Personal profile

Academic Biography

Jichun holds a Ph.D. degree in mechanical engineering from King’s College London, University of London, U.K. He Received a B.Eng. (Hons.) degree the M. Eng. degree in mechatronic engineering from China University of Geosciences (Wuhan). His research are focused on medical devices and robots, electric car battery, Not-destructive Testing, operational management & Intelligent transportation, IoT and AI solutions for bespoke robotics in chemical, environmental, life science, energy and agri-food industries. He worked on projects from EU, EPSRC and Innovate UK on biomass sampling handing robotics and Li-ion battery measurement and modeling most recently. He is a member of IEEE, IET and IMeChE.

 

Fingerprint Dive into the research topics where Jichun Li is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Neural networks Engineering & Materials Science
Recurrent neural networks Engineering & Materials Science
Chemical activation Engineering & Materials Science
Fourier transform infrared spectroscopy Engineering & Materials Science
Robots Engineering & Materials Science
Liquids Engineering & Materials Science
Washing Engineering & Materials Science
Evolutionary algorithms Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2019 2019

73 Downloads (Pure)

An Improved Complex-Valued Recurrent Neural Network Model for Time-Varying Complex-Valued Sylvester Equation

Ding, L., Xiao, L., Zhou, K., Lan, Y., Zhang, Y. & Li, J., 1 Feb 2019, In : IEEE Access. 7, p. 19291-19302 12 p., 8632909.

Research output: Contribution to journalArticle

Open Access
File
Recurrent neural networks
Neural networks
Chemical activation
Sampling
Experiments
49 Downloads (Pure)

A Fully Automated Robot for the Preparation of Fungal Samples for FTIR Spectroscopy Using Deep Learning

Xiong, Y., Shapaval, V., Kohler, A., Li, J. & From, P. J., 16 Sep 2019, In : IEEE Access. 7, p. 132763-132774 12 p.

Research output: Contribution to journalArticle

Open Access
File
Fourier transform infrared spectroscopy
Robots
Liquids
Washing
Syringes

A new noise-tolerant and predefined-time ZNN model for time-dependent matrix inversion

Xiao, L., Zhang, Y., Dai, J., Chen, K., Yang, S., Li, W., Liao, B., Ding, L. & Li, J., 30 Sep 2019, In : Neural Networks. 117, p. 124-134 11 p.

Research output: Contribution to journalArticle

Neural Networks (Computer)
Noise
Neural networks
Manipulators
Chemical activation
10 Downloads (Pure)

A Noise Tolerant Zeroing Neural Network for Time-Dependent Complex Matrix Inversion Under Various Kinds of Noises

Xiao, L., Zhang, Y., Zuo, Q., Dai, J., Li, J. & Tang, W., 22 Aug 2019, In : IEEE Transactions on Industrial Informatics. 9 p.

Research output: Contribution to journalArticle

Open Access
File
Neural networks
Computer simulation
55 Downloads (Pure)

Design and Analysis of Two FTRNN Models with Application to Time-Varying Sylvester Equation

Jin, J., Xiao, L., Lu, M. & Li, J., 15 Apr 2019, In : IEEE Access. 7, p. 58945-58950 6 p., 8691448.

Research output: Contribution to journalArticle

Open Access
File
Recurrent neural networks
Neural networks
Computer simulation