Professor Xiaohui Liu (PhD, CEng, FBCS)
College of Engineering, Design and Physical Sciences
I joined Brunel as Professor of Computing in 2000. Prior to that, I was a member of academic staff at Birkbeck, University of London in Computer Science and research staff at Durham and Heriot-Watt Universities in Engineering. At Brunel, I was Director of Research for the School of Information Systems, Computing and Mathematics (2006-2014) and Doctoral Programme Director for Computer Science (2008-2013).
My research interests include the construction of computationally intelligent algorithms, software and systems as well as the integration, analysis and visualisation of large-scale, fast evolving real-world complex data. I chaired the first (see the conference report) & second International Symposia on Intelligent Data Analysis in 1995 & 1997. More recently, I have been calling for the introduction of a new A-level course in the UK on Data Analytics to lay a firm foundation for next generation data scientists in light of Big Data (see an official report: A World Full of Data by Roger Porkess, launched by the Royal Statistical Society and the Institute and Faculty of Actuaries on 11 September 2013).
I have advised funding agencies on interdisciplinary research programmes in data analytics, genomics and security as well as served on grant panels of research councils in the UK, including the BBSRC, EPSRC and NERC. Recently I have been named as a 2016 Highly Cited Researcher (HCR), based on the citation data for the journals indexed in the Web of Science during the 11-year period 2004-2014. Previously I was also included in the list of Thomson Reuters HCRs in 2014 and in 2015.
News: Miqing Li, a PhD student at the Centre for Intelligent Data Analysis, was announced as the winner of the Best Student Paper award at the IEEE Congress on Evolutionary Computation (CEC-2014) for the paper entitled “A Test Problem for Visual Investigation of High-Dimensional Multi-Objective Search”.
o G Huang, X Liu, J He, F Klawonn, and G Yao (Eds.), “Health Information Science”, Lecture Notes in Computer Science 7798, Springer, 2013
o K Fraser, Z Wang and X Liu, "Microarray Image Analysis: an Algorithmic Approach", Chapman & Hall/CRC, 2010.
o S Chen, R Macredie, X Liu, and A Sutcliffe, Special Issue on “Data Mining for Understanding User Needs”, ACM Transactions on Computer-Human Interaction, 17(1), 2010.
o Z Wang and X Liu (Eds), Special issue on "Intelligent Computation for Bioinformatics", IEEE Transactions on Systems, Man, and Cybernetics - Part C, 38(1), 2008.
o F Famili, X Liu and J Pena (Eds), Proceedings of the ECAI Workshop on Data Mining in Functional Genomics and Proteomics: Current Trends and Future Directions, Valencia, 2004.
o R Bellazzi, B Zupan and X Liu (Eds), Proceedings of the 6th International Workshop on Intelligent Data Analysis in Medicine and Pharmacology, London, 2001.
o X Liu (Ed), Special Issue on “Progress in Intelligent Data Analysis”, International Journal of Applied Intelligence, 11(3), 1999.
o X Liu, P Cohen and M Berthold (Eds), Special Issue on “Reasoning about Data”, Intelligent Data Analysis: an International Journal, 2(2), 1998.
o X Liu, P Cohen and M Berthold (Eds), "Advances in Intelligent Data Analysis", Lecture Notes in Computer Science 1280, Springer, 1997.
Chapters in Encyclopedia and Books
o X Liu (2005) "Intelligent Data Analysis", Encyclopedia of Data Warehousing and Mining, 634-638.
o S Chen and X Liu (2004) "Data Mining in Practice", Encyclopedia of Information Science and Technology, 723-728.
o X Liu and P Kellam (2003) "Mining Gene Expression Data", Bioinformatics: Genes, Proteins & Computers, C A Orengo, D T Jones & J M Thornton (Eds), BIOS Scientific Publishers, 229-244.
o X Liu (2003) "IDA Systems and Applications", Intelligent Data Analysis: an Introduction, M Berthold and D J Hand (Eds), 2nd edition, Springer-Verlag, 429-444.
Papers in Refereed Journals
o M Li, S Yang, and X Liu (2016), “Pareto or Non-Pareto: Bi-Criterion Evolution in Multi-Objective Optimization”, IEEE Transactions on Evolutionary Computation, in press.
o R Hierons, M Li, X Liu, S Segura, and W Zheng (2016), “SIP: Optimal Product Selection from Feature Models Using Many Objective Evolutionary Optimisation”, ACM Transactions on Software Engineering and Methodology, in press
o L Zou, Z Wang, H Gao and X Liu (2016), “State Estimation for Discrete-Time Dynamical Networks with Time-Varying Delays and Stochastic Disturbances under the Round-Robin Protocol”, IEEE Transactions on Neural Networks and Learning Systems, in press.
o D Chen, Y Tian and X Liu (2016) “Structural Non-Parallel Support Vector Machine for Pattern Recognition”, Pattern Recognition, 60:296-305.
o W Zheng, R Hierons, M Li, X Liu, and V Vinciotti (2016), “Multi-Objective Optimisation for Regression Testing”, Information Sciences, 334-335:1-16.
o J Xie, H Gao, W Xie, X Liu, and P Grant (2016), “Robust clustering by detecting density peaks and assigning points based on fuzzy weighted K-nearest neighbours”, Information Sciences, 354:19-40.
o M Li, S Yang and X Liu (2015), “Bi-Goal Evolution for Many-Objective Optimization Problems”, Artificial Intelligence, 228: 45-65.
o L Hu, Z Wang and X Liu, “Dynamic State Estimation of Power Systems with Quantization Effects: a Recursive Filter Approach”, IEEE Transactions on Neural Networks and Learning Systems, in press
o Z Zhu, G Zhang, M Li and X Liu (2016)“Evolutionary Multi-Objective Workflow Scheduling in Cloud”, IEEE Transactions on Parallel and Distributed Systems, 27(5):1344-1357.
o L Zou, Z Wang, H Gao and X Liu, “Event-Triggered State Estimation for Complex Networks with Mixed Time Delays via Sampled Data Information: the Continuous-Time Case”, IEEE Transactions on Cybernetics, in press.
o L Hu, Z Wang, I Rahman and X Liu (2016) “A Constrained Optimization Approach to Dynamic State Estimation for Power Systems Including PMU Measurements”, IEEE Transactions on Control Systems Technology, 24(2):703-710.
o D Kaba, Y Wang, C Wang, X Liu, H Zhu, A G Salazar-Gonzalez and Y Li (2015) “Retina Layer Segmentation Using Kernel Graph Cuts and Continuous Max-Flow”, Optics Express, 23(6):7366-84.
o C Cai, Z Wang, J Xu, X Liu and F Alsaadi (2015) “An Integrated Approach to Global Synchronization and State Estimation for Nonlinear Singularly Perturbed Complex Networks”, IEEE Transactions on Cybernetics, 45(8) :1597-1609.
o A Tarhini, K Hone and X Liu (2015) “A Cross‐Cultural Examination of the Impact of Social, Organisational and Individual Factors on Educational Technology Acceptance between British and Lebanese University Students”, British Journal of Educational Technology, 46(4): 739-755.
o M Li, S Yang, and X Liu (2014) “Shift-Based Density Estimation for Pareto-Based Algorithms in Many-Objective Optimization”, IEEE Transactions on Evolutionary Computation, 18(3): 348-365, 2014.
o M Li, S Yang, J Zheng, and X Liu (2014) “ETEA: A Euclidean Minimum Spanning Tree-Based Evolutionary Algorithm for Multiobjective Optimization”, Evolutionary Computation, 22(2):189-230.
o N Zeng, Z Wang, B Zineddin, Y Li, M Du, L Xiao, X Liu and T Young (2014) “Image-based Quantitative Analysis of Gold Immunochromatographic Strip via Cellular Neural Network Approach”, IEEE Transactions on Medical Imaging, 33 (5) : 1129- 1136
o M Li, S Yang, K Li and X Liu (2014) “Evolutionary Algorithms with Segment-based Search for Multi-objective Optimization Problems”, IEEE Transactions on Cybernetics, 44(8): 1295-1313.
o M Li, S Yang and X Liu (2014) “Diversity Comparison of Pareto Front Approximations in Many-Objective Optimization”, IEEE Transactions on Cybernetics, 44(12):2568-2584.
o A Tarhini, K Hone and X Liu (2014) “The Effects of Individual Differences on E-learning Users’ Behaviour in Developing Countries: A Structural Equation Model”, Computers in Human Behavior, 41: 153-163.
o J He, X Liu, G Huang, M Blumenstein, and C Leung (2014) “Current and Future Development of Big Data in Commonwealth Countries”, The Bridge, 44(4):38-45, US National Academy of Engineering, Winter 2014.
o A Salazar-Gonzalez, D Kaba, Y Li and X Liu (2014) “Segmentation of Blood Vessels and Optic Disc in Retinal Images”, IEEE Journal of Biomedical and Health Informatics, 18(6):1874-1886.
o Y Tian, Z Qi, X Ju, Y Shi, X Liu (2014), “Nonparallel Support Vector Machines for Pattern Classification”, IEEE Transactions on Cybernetics, 44 (7), 1067-1079.
o N Zeng, Z Wang, Y Li, M Du, J Cao and X Liu (2013) “Time Series Modelling of Nano-Gold Immunochromatographic Assay via Expectation Maximization Algorithm”, IEEE Transactions on Biomedical Engineering, 60(12):3418-3424.
o P Louvieris, N Clewley, and X Liu (2013), “Effects-Based Feature Identification for Network Intrusion Detection”, Neurocomputing, 121:265-273.
o Z Wang, H Wu, J Liang, J Cao and X Liu (2013), “On modeling and state estimation for genetic regulatory networks with polytopic uncertainties”, IEEE Transactions on NanoBioscience, 12 (1) : 13- 20
o R Alhajri, S Counsell and X Liu (2013) “Investigating attributes affecting the performance of WBI users”, Computers & Education 68: 117-128.
o S Yang, M Li, X Liu, and J Zheng (2013) “A Grid-Based Evolutionary Algorithm for Many-Objective Optimization”, IEEE Transactions on Evolutionary Computation, 17(5):721-736.
o Z Wang, J Eatock, S McClean, D Liu, X Liu and T Young (2013), “Modeling Throughput of Emergency Departments via Time Series: an Expectation Maximization Algorithm”, ACM Transactions on Management Information Systems, 4(4), Art. No. 16, doi: 10.1145/2544105.
o Y Liu, Z Wang, J Liang and X Liu (2013), “Synchronization of Coupled Neutral-Type Neural Networks with Jumping-Mode-Dependent Discrete and Unbounded Distributed Delays”, IEEE Transactions on Cybernetics, 43:102-114.
o J Liang, Z Wang, X Liu and P Louvieris (2012), “Robust synchronization for two-dimensional discrete-time coupled dynamical networks”, IEEE Transactions on Neural Networks and Learning Systems, 23(6):942-953
o B Shen, Z Wang and X Liu (2012), “Sampled-Data Synchronization Control of Complex Dynamical Networks with Stochastic Sampling”, IEEE Transactions on Automatic Control, 57(10):2644-2650.
o J Liang, Z Wang, B Shen and X Liu, (2012) “Distributed State Estimation in Sensor Networks with Randomly Occurring Nonlinearities Subject to Time-Delays”, ACM Transactions on Sensor Networks, 9(1), doi: 10.1145/2379799.2379803.
o N Zeng, Z Wang, Y Li, M Du, and X Liu (2012), “A Hybrid EKF and Switching PSO Algorithm for Joint State and Parameter Estimation of Lateral Flow Immunoassay Models”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(2):321-329
o C Wei, S Chen, and X Liu (2012) “Mammogram Retrieval on Similar Mass Lesions”. Computer Methods and Programs in Biomedicine, 106:234-248.
o B Shen, Z Wang, and X Liu (2011), “Bounded H-infinity Synchronization and State Estimation for Discrete Time-Varying Stochastic Complex Networks over a Finite Horizon” IEEE Transactions on Neural Network 22(1):145-157.
o N Zeng, Z Wang, Y Li, M Du, and X Liu (2011), “Inference of Nonlinear State-Space Models for Sandwich-Type Lateral Flow Immunoassay Using Extended Kalman Filtering”, IEEE Transactions on Biomedical Engineering, 58(7) : 1959- 1966.
o B Zineddin, Z Wang and X Liu (2011), “Cellular Neural Networks, Navier-Stokes Equation and Microarray Image Reconstruction”, IEEE Transactions on Image Processing, 20 (11):3296- 3301.
o J Liang, Z Wang, and X Liu (2011), “Distributed State Estimation for Discrete-Time Sensor Networks with Randomly Varying Nonlinearities and Missing Measurements”, IEEE Transactions on Neural Networks 22(3):486-496.
o A Ruta, Y Li, and X Liu (2010) “Real-Time Traffic Sign Recognition from Video by Class-Specific Discriminative Features”, Pattern Recognition 43 (1) : 416- 430
o N Clewley, S Chen, and X Liu (2010), “Cognitive Styles and Search Engine Preferences: Field Dependence/Independence vs Holism/Serialism”, Journal of Documentation 66 (4) : 585- 603.
o Z. Wang, Y. Wang and Y. Liu (2010), “Global synchronization for discrete-time stochastic complex networks with randomly occurred nonlinearities and mixed time-delays”, IEEE Transactions on Neural Network, 21(1):11-25.
o J Liang, Z Wang, and X Liu (2010) “On Passivity and Passification of Stochastic Fuzzy Systems with Delays: the Discrete-Time Case”, IEEE Transactions on Systems, Man and Cybernetics, Part B 40 (3) : 964- 969
o A Ruta, Y Li, and X Liu (2010), “Robust Class Similarity Measure for Traffic Sign Recognition”, IEEE Transactions on Intelligent Transportation Systems 11 (4) : 846- 855
o Z Wang, Y Liu, G Wei and X Liu (2010), “A note on control of a class of discrete-time stochastic systems with distributed delays and nonlinear disturbances”, Automatica, 46(3):543-548
o J Liang, Z Wang, X Liu (2009) “Global Synchronization in an Array of Discrete-Time Neural Networks with Nonlinear Coupling and Time-Varying Delays”, International Journal of Neural Systems 19(1): 57-63.
o J Liang, Z Wang and X Liu (2009), "State Estimation for Coupled Uncertain Stochastic Networks with Missing Measurements and Time-Varying Delays: The Discrete-Time Case", IEEE Transactions on Neural Networks, 20 (5) : 781- 793.
o Z Wang, X Liu, Y Liu, J Liang and V Vinciotti (2009) "An Extended Kalman Filtering Approach to Modelling Nonlinear Dynamic Gene Regulatory Networks via Short Gene Expression Time Series", IEEE/ACM Transactions on Computational Biology and Bioinformatics, 6 (3): 410- 419.
o Y Liu, Z Wang, J Liang and X Liu (2009) “Stability and synchronization of discrete-time Markovian jumping neural networks with mixed mode-dependent time-delays”, IEEE Transactions on Neural Networks, 20(7):1102-1116.
o F Yang, Z Wang, G Feng and X Liu (2009), “Robust Filtering with Randomly Varying Sensor Delay: The Finite-Horizon Case”, IEEE Transactions on Circuits and Systems – Part I, 56(3):664-672.
o G Wei, Z Wang, J Lam, K Fraser, G Rao, and X Liu, (2009) “Robust filtering for stochastic genetic regulatory networks with time-varying delay”, Mathematical Biosciences 220 (2) :73- 80
o Y Liu, Z Wang and X Liu (2009) "Asymptotic Stability for Neural Networks with Mixed Time-Delays: the Discrete-Time Case", Neural Networks, 22(1):67- 74.
o W Sheng, X Liu and M Fairhurst (2008), "A Niching Memetic Algorithm for Simultaneous Clustering and Feature Selection", IEEE Transactions on Knowledge and Data Engineering, 20:868-879.
o Z Wang, J Lam, G Wei, K Fraser and X Liu (2008), "Filtering for Nonlinear Genetic Regulatory Networks with Stochastic Disturbances", IEEE Transactions on Automatic Control, 53: 2448-2457.
o J Liang, Z Wang, Y Liu and X Liu (2008), "Robust Synchronization of an Array of Coupled Stochastic Discrete-Time Delayed Neural Networks", IEEE Transactions on Neural Networks, 19:1910-1921.
o J Liang, Z Wang, Y Liu and X Liu (2008), “Global Synchronization Control of General Delayed Discrete-Time Networks with Stochastic Coupling and Disturbances”, IEEE Transactions on Systems, Man, and Cybernetics - Part B, 38:1073-1083.
o S Chen and X Liu (2008), "An Integrated Approach for Modeling Learning Patterns of Students in Web-Based Instruction: A Cognitive Style Perspective", ACM Transactions on Computer Human Interaction, 15(1):1-28.
o Z Wang, F Yang, D Ho, S Swift, A Tucker and X Liu (2008), "Stochastic Dynamic Modelling of Short Gene Expression Data", IEEE Transactions on Nanobioscience, 7:44-55.
o M Hirsch, S Swift and X Liu (2007) "Optimal Search Space for Clustering Gene Expression Data via Consensus", Journal of Computational Biology, 14(10):1327-1341.
o E Panteris, S Swift, A Payne and X Liu (2007), "Mining Pathway Signatures from Microarray Data and Relevant Biological Knowledge", Journal of Biomedical Informatics, 40(6):698-706.
o E Frias-Martinez, S Chen, R Macredie and X Liu (2007), "The Role of Human Factors in Stereotyping Behavior and Perception of Digital Library Users: a Robust Clustering Approach", User modeling and User-Adapted Interaction, 17:305-337.
o Z Wang, F Yang, D Ho, and X Liu (2007) "Robust H-infinity Control for Networked Systems with Random Packet Losses", IEEE Transactions on Systems, Man and Cybernetics - Part B, 37:916-924.
o E Frias-Martinez, S Chen, and X Liu (2007) "Automatic Cognitive Style Identification of Digital Library Users for Personalization", Journal of the American Society for Information Science and Technology, 58:237-251.
o Y Liu, Z Wang, A Serrano and X Liu (2007) “Discrete-time Recurrent Neural Networks with Time-Varying Delays”, Physics Letters A, 362:480-488.
o V Vinciotti, X Liu, R Turk, E de Meijer and P t Hoen (2006) "Exploiting the Full Power of Temporal Gene Expression Profiling through a New Statistical Test: Application to the Analysis of Muscular Dystrophy Data", BMC Bioinformatics, 7:183.
o Z Wang, Y Liu, M Li, and X Liu (2006) "Stability Analysis for Stochastic Cohen-Grossberg Neural Networks with Mixed Time Delays", IEEE Transactions on Neural Networks, 27:814-820.
o F Yang, Z Wang, D Ho and X Liu (2006) "Robust H-2 Filtering for A Class of Systems with Stochastic Nonlinearities", IEEE Transactions on Circuits and Systems - Part II: Analog and Digital Signal Processing, 53:235-239.
o E Frias-Martinez, S Chen and X Liu (2006) "Survey of Data Mining Approaches to User Modeling for Adaptive Hypermedia", IEEE Transactions on Systems, Man, and Cybernetics: Part C, 36:734-749.
o Z Wang, F Yang, D Ho and X Liu (2006) "Robust H-infinity Filtering for Stochastic Time-Delay Systems with Missing Measurements", IEEE Transactions on Signal Processing, 54: 2579-2587.
o Y Liu, Z Wang, and X Liu (2006) "Global Exponential Stability of Generalized Recurrent Neural Networks with Discrete and Distributed Delays", Neural Networks, 19:667-675.
o Z Wang, Y Liu, L Yu and X Liu (2006) “Exponential Stability of Delayed Recurrent Neural Networks with Markovian Jumping Parameters”, Physics Letters A, 356:346-352
o P O'Neill, K Fraser, Z Wang, P Kellam, J Kok, and X Liu (2005) "Pyramidic Clustering of Large Scale Microarray Images", The Computer Journal, 48:466-479.
o A Tucker, V Vinciotti, X Liu and D Garway-Heath (2005) "A Spatio-Temporal Bayesian Network Classifier for Understanding Visual Field Deterioration", Artificial Intelligence in Medicine, 34:163-177.
o V Vinciotti, R Khanin, D DAlimonte, X Liu, N Cattini, G Bucca, O de Jesus, J Rasaiyaah, C Smith, P Kellam and E Wit (2005) "An Experimental Evaluation of Loop versus Reference Design for Two-Channel Microarrays", Bioinformatics, 21:492-501.
o Z Wang, D Ho and X Liu (2005) "State Estimation for Delayed Neural Networks", IEEE Transactions on Neural Networks, 16:279-284.
o W Sheng, S Swift, L Zhang and X Liu (2005) "A Weighted Sum Validity Function for Clustering With a Hybrid Niching Genetic Algorithm", IEEE Transactions on Systems, Man and Cybernetics - Part B, 35:1156-1167.
o S Swift, A Tucker, V Vinciotti, N Martin, C Orengo, X Liu and P Kellam (2004) "Consensus Clustering and Functional Interpretation of Gene Expression Data", Genome Biology, 5:R94.
o S Chen and X Liu (2004) "The Contribution of Data Mining to the Field of Information Science", Journal of Information Science, 30:550-558.
o A Tucker and X Liu (2004) "A Bayesian Network Approach to Explaining Time Series with Changing Structure", Intelligent Data Analysis, 8:460-480.
o Z Wang, J Lam and X Liu (2003) "Nonlinear Filtering for State Delayed Systems with Markovian Switching", IEEE Transactions on Signal Processing, 51:2321-2328.
o P O'Neill, G Magoulas and X Liu (2003) "Improved Processing of Microarray Data Using Image Reconstruction Techniques", IEEE Transactions on Nanobioscience, 2(4):176-183.
o Z Wang, D Ho and X Liu (2003) "Variance-Constrained Filtering for Uncertain Stochastic Systems with Missing Measurements", IEEE Transactions on Automatic Control, 48:1254-1258.
o X Liu, G Cheng and J Wu (2002) "Analysing Outliers Cautiously", IEEE Transactions on Knowledge and Data Engineering, 14:432-437.
o Swift and X Liu (2002) "Predicting Glaucomatous Visual Field Deterioration Through Short Multivariate Time Series Modelling", Artificial Intelligence in Medicine, 24:5-24.
o S Swift, A Tucker, N Martin and X Liu (2001) “Grouping Multivariate Time Series Variables: Applications to Chemical Process and Visual Field Data”, Knowledge-Based Systems, 14, 147-154.
o A Tucker, S Swift and X Liu (2001) "Variable Grouping in Multivariate Time Series via Correlation", IEEE Transactions on Systems, Man and Cybernetics - Part B, 31:235-245.