University of Nottingham Malaysia
School of Computer Science

Neural Computation


This research aims to understand and contribute to both biological and artificial neural computation. On the biological side, several models of the retina are being developed for the extraction of image processing algorithms and the design of retinal prostheses. On the artificial side new neural architectures are being developed and researched which are inspired by the computational diversity of biological neurons.  Neural network based solutions for the segmentation of histological data for the 3D reconstruction of neural circuits are also being investigated.  NeuralFig1-200

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Current projects

Neural computation projects

Title: Recurrent Analogue Neural Networks for Retinal Modelling.
PhD Student: Jung Ren Lee (e-mail: khyx9ljr*).
Aim: to develop models of the outer retina in order to understand early retinal computation and extract image processing algorithms.
More information: research poster [pdf]


Title: Retinal Modelling for the Design of Retinal Prostheses.
PhD Student: Tran Trung Kien (e-mail: khyx1ttk*).
Aim: to model the inner retina in order to understand late retinal computation and design retinal prostheses with new capabilities.
More information: research poster [pdf]


Title: Neural Network Image Segmentation for Retinal Circuit Reconstruction.
PhD Student: Rajeswari Raju (e-mail: khyx1rru*).
Aim: to develop novel neural network based segmentation techniques specifically for the 3D reconstruction of neural circuits.
More information: research poster [pdf].


Title: Improving the Optimization of Neural Diversity Machines.
PhD Student: Abdullahi Adamu (e-mail: khyx1asa*).
Aim: to develop new optimization and/or learning strategies for improving the convergence and generalization properties of Neural Diversity Machines.
More information: research poster [pdf].


Title: Simulation modelling of nanoparticle assembly formation.
Collaborators: Andrzej Bargiela, Yuying Yan and Nan Gao.
Aim: to simulate nanoparticle assembly formation to guide the development of novel nano-coatings for retinal prostheses.



Grant: Fundamental Research Grant Scheme (Ministry of Higher Education, Malaysia)
Title: Large-Scale Retinal Modeling for the Design of New Generation Retinal Prostheses
Amount: RM 63,000 
Dates: from 4th Oct 2010 to 4th Oct 2013

Grant: The Logistics of Small Things, A Cross-disciplinary Feasibility Account (EPSRC)
Title: Interdisciplinary Developments of Retinal Prostheses
Amount: £8,000
Dates: from 7th Feb 2011 to 30th April 2011

Selected publications

  1. Barteczko-Hibbert, C; Gillott, M and Kendall, G An artificial neural network for predicting domestic hot water characteristics. International Journal of Low-Carbon Technologies, 4 (2): 112-119, 2009.
  2. Binner, J.M; Gazely, A.M and Kendall, G An evaluation of UK risky money: an artificial intelligence approach. Global Business and Economics Review, 11 (1): 1-18, 2009.
  3. Binner, J; Kendall, G and Gazely, A Evolving Neural Networks with Evolutionary Strategies: A New Application to Divisa Money. Advances in Econometrics, 19: 127-143, 2004.
  4. Kendall, G and Su, Y Imperfect Evolutionary Systems. IEEE Transactions on Evolutionary Computation, 11 (3): 294-307, 2007.
  5. Kien, T.T., Maul, T.H. and Bargiela, A., 2011. A Review of Retinal Prosthesis Approaches. In: International Conference on Mathematical and Computational Biology.
  6. Maul, T.H., 2011. Early Experiments with Neural Diversity Machines. Manuscript submitted for publication.
  7. Maul T., Bargiela A., Ren L.J., 2011. Cybernetics of Vision Systems: Towards an Understanding of Putative Functions of the Outer Retina. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 41(3), 398-409.
  8. Maul, T.H., Bargiela, A., Yan, Y. and Gao, N., 2011. Simulation Modelling of Nanoparticle Assemblies Formed by Spray Deposition. In: 25th European Conference on Modelling and Simulation.
  9. Maul, T.H. & Baba, S., 2010. Unsupervised Learning in Second-Order Neural Networks for Motion Analysis. Neurocomputing, 74(6), 884-895.
  10. Maul, T.H., Bargiela, A., Ren, L.J. A Neuroalgorithmic Investigation of the Outer Retina. Accepted for publication in the European Conference on Modelling and Simulation, June 2010.
  11. Maul, T.H. & Baba, S. Neural Clustering of Correspondences for Visual Pose Estimation. Proceedings of 23rd European Conference on Modelling and Simulation, Madrid, 2009.
  12. Maul, T.H., Baba, S. & Yusof, A. Structural Optimization of Second Order Neural Networks for Pose Estimation. Proceedings of International Conference on Robotics, Vision, Information and Signal Processing, Penang, November, 2007.
  13. Shengxiang Yang, Dingwei Wang, Tianyou Chai, Graham Kendall: An improved constraint satisfaction adaptive neural network for job-shop scheduling. J. Scheduling 13(1): 17-38 (2010)
  14. Ward, C.R; Gobet, F and Kendall, G Evolving Collective Behavior in an Artificial Ecology. Artificial Life, 7 (2): 191-209, 2001.

Academic Staff

  • Tomas Maul (webpage, e-mail: Tomas.Maul*)
  • Graham Kendall (webpage, e-mail: Graham.Kendall*)


School of Computer Science

University of Nottingham Malaysia
Jalan Broga, 43500 Semenyih
Selangor Darul Ehsan

telephone: +6 (03) 8924 8000
fax: +6 (03) 8924 8018

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