Professor Xiaohui Liu (PhD, CEng, FBCS)
College of Engineering, Design and Physical
Sciences Department of Computer Science,
Brunel University London UB8 3PH,
United Kingdom Fax:
(+44)(0)1895 251686 Email: Xiaohui.Liu@brunel.ac.uk I joined Brunel as Professor of Computing
in 2000. Prior to that, I was a member of academic staff in computer science
at Birkbeck, University of London and research
staff in engineering at Durham and Heriot-Watt Universities. At Brunel, I was
Director of Research (2006-14) for the School of Information Systems,
Computing and Mathematics, Doctoral Programme Director (2008-13) and Chair of
Industry Advisory Board (2016-18) for Computer
Science. |
|
|
I received a BEng in Computing
from Hohai University, Nanjing, and PhD in Computer
Science from Heriot-Watt University, Edinburgh. A Chartered Engineer,
Chartered Fellow of British Computer Society, Fellow of Royal Statistical
Society, and Life Member of the Association for the Advancement of Artificial
Intelligence, I was honorary Pascal professor in Leiden University (2004),
visiting scientist at Harvard Medical School (2005) and visiting professor in
the Chinese Academy of Sciences (2010). My research interests include
artificial intelligence and data science, with applications in biology,
business, engineering and healthcare. In collaboration with many talented
researchers in academia and industry, I have published more than 300 papers,
with over 200 in journals including Artificial Intelligence, Neural Networks, Pattern Recognition, Genome
Biology, ACM and IEEE
Transactions. My work has been in part funded by UK research councils, EU, charities and industry, and
currently I am a member of two EC H2020 innovative manufacturing teams
working on Z-BRE4K (2017-21; €6M) and INTEGRADDE
(2018-22; €12.7M). I founded the International
Symposium on Intelligent Data Analysis
(see IDA-95
& IDA-97), and gave keynote addresses at international conferences in
computing, data science, pattern recognition, and statistics. I advised
RCUK on data analytics, genomics and security, and the Royal Statistical
Society / the Institute and Faculty of Actuaries on statistical
education at UK schools in light of big data. I served on grant/fellowship panels of RCUK (e.g. BBSRC, EPSRC
and NERC), and during 2015-16, I was on the international panel to assess the
quality of computer science research between 2009 and 2014 in the
Netherlands. I have
been named as a Highly Cited Researcher annually since
2014 [by Thomson Reuters 2014-15, and Clarivate
Analytics 2016-18], based on the number of Highly Cited Papers indexed in the
Web of Science during the preceding 11-years. Highly Cited Papers are defined
as those that rank in the top 1% by citations for field and publication year
in the Web of Science. |
|
Research Grants/Projects
o
AHRC,
“Cognitive Personalised Interfaces for Web-based Library Catalogues”, Co-Investigator,
in collaboration with Sherry Chen and Rob Macredie.
o
BBSRC,
“Novel Algorithms for Gene Expression Time Series”, Principal Investigator,
with Nigel Martin (Birkbeck), Paul Kellam and Christine Orengo
(UCL).
o
BBSRC,
“Analysing Virus Gene Expression Data to Understand Regulatory Interactions”,
Principal Investigator, with Nigel Martin (Birkbeck),
Paul Kellam and Christine Orengo
(UCL).
o
BBSRC, “DNA
Microarray Data Analysis: an Integrated Approach”, Principal Investigator, with
Olaf Wolkenhauer, David Broomhead
& Mark Muldoon (Manchaster), Paul Kellam (UCL), David Lowe and Ian Nabney
(Aston), Ernst Wit (Glasgow), and Colin Smith (Surrey).
o
BBSRC,
“Bayesian Networks for Modelling Gene Expression Data”, visiting scientist at
Harvard Medical School and observer
in Children's Hospital Boston, Principal
Investigator, with Marco Ramoni (Harvard/CHB).
o
British
Council for Prevention of Blindness, “The Neural Network Development of the
Wu-Jones Test”, Principal Investigator, with Barrie Jones and John Wu (UCL/Moorfields
Eye Hospital).
o
Central
Middlesex Hospital/North Thames Regional Health Authority/EPSRC CASE Award,
“Haemoglobin Identification by Artificial Intelligence”, Principal
Investigator, with Sally C Davies & Joan S Heathorn
(CMH/Imperial).
o
DSTL, “Intent
Mining Analytical Tools for Cyber Defence”, Co-Investigator, with Panos Louvieris and Zidong Wang
o
DSTL,
“Smarter IntelligEnce Visualisation Environment”
Co-Investigator, Panos Louvieris
and Zidong Wang
o
EC Horizon 2020, INTEGRADDE: “Intelligent
Data-Driven Pipeline for the Manufacturing of Certified Metal Parts through
Direct Energy Deposition Processes”, Co-Investigator,
with Zidong Wang, Stasha Lauria and others.
o
EC Horizon
2020, Z-BRE4K: “Real-Time Adaptable Machine Simulation models wrapped around Physical
Systems for Accurate Predictive Maintenance, towards Zero Unexpected Breakdowns
and Increased Operating Life of Factories”, Co-Investigator, with Ali Mousavi, Zidong Wang, Maozhen Li and
others.
o
EC FP7,
EWATUS: “An Integrated Support System for Efficient Water Usage and Resources
Management”, Co-Investigator, with Andrea Capiluppi, Zidong Wang and others.
o
EC FP7,
EFACTS: “European Friedreich’s Ataxia Consortium for Translational Studies”,
Co-Investigator, with Mark Pook, David Gilbert,
Annette Payne and others.
o
EPSRC, “Reconstructing
Background of DNA Microarray Images”, Principal Investigator, with Yongmin Li, Zidong Wang and Paul Kellam (UCL/Sanger).
o
EPSRC,
“Explaining Multivariate Time Series to Detect Early Problem Signs”, Principal
Investigator.
o EPSRC, “Modelling Short Multivariate Time Series”,
Principal Investigator.
o
EPSRC,
“Human Factors in the Design of Adaptive Hypermedia Systems: A Cognitive Style
Approach”, Co-Investigator, with Sherry Chen and Rob Macredie.
o
EPSRC, “An
Automated System for Chemical Structure Characterisation for Mass
Spectrometry”, Co-Investigator, with Roger Johnson (Birkbeck)
and Alan Payne (Kodak).
o
EPSRC CASE
Award/GSK, “Predicting Chromatin Status
from Differential Expression Profiles”, Principal Investigator, with David
Gilbert and Paul Wilson (GSK).
o EPSRC CASE Award/Honeywell/BP, “Casual
Modelling for Time Series Data”, Principal Investigator, with Andrew
Ogden-Swift (Honeywell UK), Tariq Samad (Honeywell
Technology Centre, USA) and Donald Campbell-Brown (BP).
o
EPSRC CASE
Award/Moorfields Eye Hospital, “Improving Glaucoma Service by Intelligent Data
analysis”, Principal Investigator, with Fred Fitzke,
Roger Hitchings , Richard Wormald
and John Wu (Moofields/UCL).
o
EPSRC CASE
Award/Optirisk, “Methods of Optimal Portfolio Construction
with Target Returns and Downside
Risk Aversion”, Principal Investigator, in collaboration with Gautam Mitra (Optirisk/Brunel).
o
National
Science Foundation of China (Major International Research Collaboration
Project), “Business Intelligence Methods Based on Optimization Data Mining with
Applications in Financial and Banking Management”, Co-Investigator, with Yong
Shi & Yingjie Tian (Chinese Academy of Sciences)
and Xiaojun Chen (Hong Kong Polytechnic University).
o
The Royal Academy
of Engineering/the Chinese Academy of Engineering, “Modelling, Quantification Analysis and Applications of Lateral
Flow Immunoassay”, Co-Investigator, with Zidong Wang,
Yurong Li & Min Du (Fuzhou).
o
The Royal
Society, “Big Data Learning-based QoS Analysis and
Estimation of Cloud-services”, Co-Investigator, with Zidong
Wang and Stasha Lauria.
o
The Wellcome Trust, “Integrating Structural and Transcriptomics
Data to Reveal Protein Functions”, Co-Investigator, with Christine Orengo, David Jones
and Paul Kellam (UCL), Janet Thornton and Alvis Brazma (European Bioinformatics Institute, Cambridge), Nigel Martin (Birkbeck)
and Mike Hubank (Institute of Child Health, London).
Books/Edited Collections
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
W Liu, Z
Wang, X Liu, N Zeng and D Bell, “A Novel Particle Swarm Optimization Approach
for Patient Clustering from Emergency Departments”, IEEE Transactions on
Evolutionary Computation, in press.
o
F Wang, Z Wang, J Liang and X Liu, “Resilient
State Estimation for Two-Dimensional Time-Varying Systems with Redundant
Channels: a Variance-Constrained Approach, IEEE
Transactions on Cybernetics, in press.
o
X Wan, Z Wang,
M Wu and X Liu, “H-infinity State Estimation for Discrete-Time Nonlinear
Singularly Perturbed Complex Networks under the Round-Robin Protocol”, IEEE
Transactions on Neural Networks and Learning Systems, in press.
o
F Wang, Z
Wang, J Liang and X Liu, “Event-Triggered Recursive Filtering for Shift-Varying
Linear Repetitive Processes”, IEEE Transactions on Cybernetics, in press
o
M Li, C Grosan, S Yang, X Liu, and X Yao (2018), “Multi-Line
Distance Minimization: A Visualized Many-Objective Test Problem Suite”, IEEE Transactions on Evolutionary
Computation, 22(1):61-78.
o
J Tang, Y
Tian, X Liu, D Li, J Lv, G Kou (2018) “Improved Multi-View
Privileged Support Vector Machine”, Neural
Networks, 106:96-109.
o
L Hu, Z
Wang, Q Han and X Liu (2018), “State Estimation under False Data Injection
Attacks: Security Analysis and System Protection, Automatica, 87:176-183.
o
M Ferdous, Y Bao, V Vinciotti, X Liu and P
Wilson (2018) “Predicting gene expression from genome wide protein binding
profiles”, Neurocomputing,
275, 1490-1499
o
J Tang, Y
Tian, and X Liu (2018), “Multiview Privileged Support
Vector Machines”, IEEE Transactions on Neural Networks and Learning
Systems, 29(8):3463-3477
o
F Wang, Z Wang, J Liang and X. Liu (2018), “A Variance-Constrained Approach to Recursive
Filtering for Nonlinear 2-D Systems With Measurement Degradations”, IEEE Transactions on
Cybernetics, 48(6):1877-1887.
o
H Liu, Z
Wang, B Shen and X Liu, (2018), “Event-Triggered State Estimation for Delayed
Stochastic Memristive Neural Networks with Missing
Measurements: the Discrete Time Case”, IEEE Transactions on Neural Networks
and Learning Systems, 29(8):3726-3737.
o
J Liang, F
Wang, Z Wang, X Liu (2018) “Robust Kalman filtering
for two-dimensional systems with multiplicative noises and measurement degradations:
The finite-horizon case”, Automatica, 96:166-177.
o
W Liu, Z
Wang, X Liu, N Zeng, Y Liu and F Alsaadi (2017), “A
survey of Deep Neural Network Structures and their Applications”, Neurocomputing,
234:11-26.
o
L Zou, Z
Wang, H Gao and X Liu (2017), “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, 28(5): 1139-1151.
o
L Hu, Z Wang
and X Liu (2016), “Dynamic State Estimation of Power Systems with Quantization
Effects: a Recursive Filter Approach”, IEEE Transactions on Neural Networks
and Learning Systems, 27(8):1604-1614.
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, 20(5):645-665.
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, 25(2).
This paper was also an invited presentation
at the 24th ACM SIGSOFT International Symposium on the Foundations of
Software Engineering (FSE-2016) and at the 39th International Conference
on Software Engineering (ICSE-2017)
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
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
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
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 Zou, Z
Wang, H Gao and X Liu (2015) “Event-Triggered State Estimation for Complex
Networks with Mixed Time Delays via Sampled Data Information: the
Continuous-Time Case”, IEEE Transactions on Cybernetics, 45
(12):2804–2815.
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
Minetou, C G, Chen, S Y, and Liu, X (2008),
“Investigation of the Use of Navigation Tools in Web-based Learning: A Data
Mining Approach”, International Journal of Human-Computer Interaction. 24(1):48-67
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.