Staff Profile

Dr Jichun Li is  a Senior Lecturer (Associate Professor) at Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University. He received his Ph.D. degree from Department of Informatics, King’s College London (top 20 world university), U.K. And then he took postdoctoral positions at Durham University, Newcastle University, Brunel University London @TWI. He joined University of Essex as a lecturer between 2020-2022.  He is a Fellow of HE and a member of IEEE and IET. 

At ICOS, He is seeking to carry out world-leading research at the interface of computing science, robotics, automation, and complex biological systems (e.g. in biology, chemistry, physics) as well as synthetic ones (e.g. in biological engineering, health care, robotics and software engineering). 

His research outputs have been published in high-impact computer science journals and international conferences, including IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Industrial Informatics, IEEE Transactions on Systems, Man, and Cybernetics,ICRA and IROS. He has led (PI/Co-I) or participated as PDRA a number of projects funded by EU, EPSRC, InnovateUK and industries which are worth about £27 millions.

 Dr Jichun Li is always looking for excellent and highly-motivated PhD students, postdoctoral researchers and visiting researchers who are interested in bio-informatics, computer science, AI, robotics and automation, nano-biotechnology, medical devices and Bio-Manufacturing. He is accepting PhD applications all year round.

      ·     PhD Studentships in School of Computing, Newcastle University

The Studentships are funded for 3/3.5/4 years depending on the project to cover the full cost of Home tuition fees, also a limited number of international fee waivers for EPSRC Studentships are available, plus a stipend bursary of £17,609 per annum

      ·     Newcastle University-China Scholarship Council (CSC) PhD Scholarship for Chinese PhD applicants

You will find the details of the CSC PhD Scholarship at Newcastle from the link below:

CSC Scholarship at Newcastle Newcastle will waive the international tuition fees and the CSC will provide the living allowance. The application will open usually every year around October. Please note this is a two-step application: Step 1: You should submit a full application (in English) to Newcastle first. You have to get an unconditional offer before you place a CSC application. The deadline for this step is usually in the early or middle of January.Step 2: If you are successful at step 1, you will then submit another full application (in Chinese) to the CSC in China. The deadline is usually in the middle of March. The result is usually announced in May. If you are successful in both steps, you will be awarded the full scholarship from Newcastle and CSC.

Research Interests

• Machine Learning
• Biotechnology
• Robotics and Automation for Scientific Instrumentation
• Nano-biotechnology
• Bio-manufacturing and Bio-informatics
• Medical devices

I have led (PI/Co-I) or participated as PDRA a number of projects funded by EU, EPSRC, Innovate UK and industries which is worth about £27 millions.

• 01/2019–03/2020 Intelligent Flexible Ultrasonic Sensing Technologies for Battery Health and Life Monitoring (GBP £ 9K)
• 06/2018–12/2018 Novel Ultrasonic Techniques for Medical Application (GBP £ 6K), Sponsor: European Regional Development Fund
• 06/2018–12/2018 Modeling ultrasonic probes-connective tissue interaction on a phantom foot model using advanced finite element method and vibration analysis towards better shockwave therapy of plantar fasciitis (GBP £ 5K) Sponsor: Early Researcher Awarded Scheme, University of Wolverhampton GBP £ 5K.
• 09/2017–03/2018 Project: Autonomous, robotic and AI-enabled biofouling monitoring, cleaning, and management System for offshore wind turbine monopile foundations. Sponsor: Innovate UK, GBP £ 700K.
•  07/2016–09/2017 Project: High Energy Density Battery (HEDB): A robotic system for online battery quality measurement using EIS method, Sponsor: Innovate UK, UK’s Advanced Propulsion Centre (APC). GBP £ 26.5 M. Consortium: Newcastle University, Nissan Motor Manufacturing Plant UK, WMG and Hyperdrive
• 10/2014–06/2016: Project: Optimal Robotic System for Tracking Mould Contamination in Juice Production Line Sponsor: EPSRC, IAA Follow-on Project. £ 80K. Consortium: Durham University, Nofima AS(Norway),Labman Automation Ltd, Synthon GMBH (Germany),Scanbi Diagnostics AB(Sweden)
• 03/2013–10/2014: Project: FP7-SME-2012: FUST “Source tracking and monitoring of mould contamination in food production: A food contamination sample handling robotic system Sponsor: EU FP7-SME. EURO €1.1M Consortium: Durham University, Nofima AS(Norway),Labman Automation Ltd, Synthon GMBH (Germany),Scanbi Diagnostics AB(Sweden), Epleblomsten AS(Norway),Elopak AS,Labnett AS(Norway).
• 03/2013–06/2016: Senior Project Leader Project: Bespoke robotic systems for life science, water, chemical and medical Applications Sponsors: Shell, P & G, Well-known Universities and research institutes

CSC8330: Advanced Programming for Digital Biology

CSC1034: Programming Portfolio 1

• Articles

  • Xia H, Zhou Y, Li J, Yue X, Li J. Outlier detection method based on improved DPC algorithm and centrifugal factor. Information Sciences 2024, 682, 121255.
  • Zhou Y, Xia H, Yu D, Cheng J, Li J. Outlier detection method based on high-density iteration. Information Sciences 2024, 662, 120286.
  • Xiao L, Jia L, Dai J, Cao Y, Li Y, Zhu Q, Li J, Liu M. Design and Analysis of a Novel Distributed Gradient Neural Network for Solving Consensus Problems in a Predefined Time. IEEE Transactions on Neural Networks and Learning Systems 2024, 35(3), 3478-3487.
  • Long J, Zhang L, Wen M, Li J, Wang K. Computation and Communication Cooperation for Molecular Microvascular Networks. IEEE Communications Letters 2024, 28(9), 2021-2025.
  • Tang W, Cai H, Xiao L, He Y, Li L, Zuo Q, Li J. A Predefined-Time Adaptive Zeroing Neural Network for Solving Time-Varying Linear Equations and Its Application to UR $5$ Robot. IEEE Transactions on Neural Networks and Learning Systems 2024, Epub ahead of print.
  • Xiao L, Wang D, Luo L, Dai J, Yan X, Li J. A Double Integral Noise-Tolerant Fuzzy ZNN Model for TVSME Applied to the Synchronization of Chua's Circuit Chaotic System. IEEE Transactions on Fuzzy Systems 2024, ePub ahead of Print.
  • Xiao L, Huang W, Li X, Sun F, Liao Q, Jia L, Li J, Liu S. ZNNs With a Varying-Parameter Design Formula for Dynamic Sylvester Quaternion Matrix Equation. IEEE Transactions on Neural Networks and Learning Systems 2023, 34(12), 9981-9991.
  • Li M, Chen J, He B, He G, Zhao C, Yuan H, Xie J, Xu G, Li J. Stimulation enhancement effect of the combination of exoskeleton-assisted hand rehabilitation and fingertip haptic stimulation. Frontiers in Neuroscience 2023, 17, 1149265.
  • Dai J, Luo L, Xiao L, Jia L, Cao P, Li J, Krasnogor N, Wang Y. Modified Noise-Immune Fuzzy Neural Network for Solving the Quadratic Programming With Equality Constraint Problem. IEEE Transactions on Neural Networks and Learning Systems 2023, epub ahead of print.
  • Xiao L, Li X, Cao P, He Y, Tang W, Li J, Wang Y. A Dynamic-Varying Parameter Enhanced ZNN Model for Solving Time-Varying Complex-Valued Tensor Inversion With Its Application to Image Encryption. IEEE Transactions on Neural Networks and Learning Systems 2023, 35(10), 13681-13690.
  • Cao P, Xiao L, He Y, Li J. A Dynamic Gain Fixed-Time Robust ZNN Model for Time-Variant Equality Constrained Quaternion Least Squares Problem With Applications to Multiagent Systems. IEEE Transactions on Neural Networks and Learning Systems 2023, epub ahead of print.
  • Hu Z, Xiao L, Li K, Li K, Li J. Performance analysis of nonlinear activated zeroing neural networks for time-varying matrix pseudoinversion with application. Applied Soft Computing 2021, 98, 106735.
  • Xiao Lin, Zhang Yongsheng, Dai Jianhua, Li Jichun, Li Weibing. New Noise-Tolerant ZNN Models With Predefined-Time Convergence for Time-Variant Sylvester Equation Solving. IEEE Transactions on Systems, Man, and Cybernetics: Systems 2021, 51(6), 3629-3640.
  • Dai J, Li Y, Xiao L, Jia L, Liao Q, Li J. Comprehensive study on complex-valued ZNN models activated by novel nonlinear functions for dynamic complex linear equations. Information Sciences 2021, 561, 101-114.
  • Hu Z, Li K, Li K, Li J, Xiao L. Zeroing neural network with comprehensive performance and its applications to time-varying Lyapunov equation and perturbed robotic tracking. Neurocomputing 2020, 418, 79-90.
  • Zhang X, Cao Y, Peng L, Li J, Ahmad N, Yu S. Mobile Charging as a Service: A Reservation-Based Approach. IEEE Transactions on Automation Science and Engineering 2020, 17(4), 1976-1988.
  • Xiao L, Dai J, Lu R, Li S, Li J, Wang S. Design and Comprehensive Analysis of a Noise-Tolerant ZNN Model With Limited-Time Convergence for Time-Dependent Nonlinear Minimization. IEEE Transactions on Neural Networks and Learning Systems 2020, 31(12), 5339-5348.
  • Zeng Y, Xiao L, Li K, Li J, Li K, Jian Z. Design and analysis of three nonlinearly activated ZNN models for solving time-varying linear matrix inequalities in finite time. Neurocomputing 2020, 390, 78-87.
  • Xiao L, Zhang Y, Zuo Q, Dai J, Li J, Tang W. A Noise-Tolerant Zeroing Neural Network for Time-Dependent Complex Matrix Inversion Under Various Kinds of Noises. IEEE Transactions on Industrial Informatics 2020, 16(6), 3757-3766.
  • Yao Y, Sun Y, Phillips C, Cao Y, Li J. Exploiting Delay Budget Flexibility for Efficient Group Delivery in the Internet of Things. IEEE Internet of Things Journal 2019, 6(4), 6593-6605.
  • Ding L, Xiao L, Zhou K, Lan Y, Zhang Y, Li J. An Improved Complex-Valued Recurrent Neural Network Model for Time-Varying Complex-Valued Sylvester Equation. IEEE Access 2019, 7, 19291-19302.
  • Xiao L, Zhang Y, Dai J, Chen K, Yang S, Li W, Liao B, Ding L, Li J. A new noise-tolerant and predefined-time ZNN model for time-dependent matrix inversion. Neural Networks 2019, 117, 124-134.
  • Xiong Y, Shapaval V, Kohler A, Li J, From PJ. A Fully Automated Robot for the Preparation of Fungal Samples for FTIR Spectroscopy Using Deep Learning. IEEE Access 2019, 7, 132763-132774.
  • Li J, Liu H, Brown M, Kumar P, Challacombe BJ, Chandra A, Rottenberg G, Seneviratne LD, Althoefer K, Dasgupta P. Ex vivo study of prostate cancer localization using rolling mechanical imaging towards minimally invasive surgery. Medical Engineering and Physics 2017, 43, 112-117.
  • Liu H, Li J, Song X, Seneviratne LD, Althoefer K. Rolling Indentation Probe for Tissue Abnormality Identification During Minimally Invasive Surgery. IEEE Transactions on Robotics 2011, 27(3), 450-460.

• Book Chapter

  • Li J, Shapaval V, Kohler A, Talintyre R, Schmitt J, Stone R, Gallant AJ, Zeze DA. A Modular Liquid Sample Handling Robot for High-Throughput Fourier Transform Infrared Spectroscopy. In: Ding, X; Kong, X; Dai, J, ed. Advances in Reconfigurable Mechanisms and Robots II. Cham: Springer International Publishing, 2016, pp.769-778.

• Conference Proceedings (inc. Abstracts)

  • Adie J, Chin C, Li J, See S. GAIANet: Accelerating Atmospheric Chemistry Modelling with Deep Learning and Fourier Neural Operators. In: SupercomputingAsia 2024. 2024, Sydney, Australia.
  • Adie J, Chin CS, Li J, See S. GAIA-Chem: a Framework for Global AI-accelerated Atmospheric Chemistry Modelling. In: PASC '24: Proceedings of the Platform for Advanced Scientific Computing Conference. 2024, Zurich, Switzerland: Association for Computing Machinery (ACM).