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Profile

College / Department

College of Engineering
Department of Computer Science and Engineering

Teaching areas

Artificial Intelligence, Machine Learning, Data Mining, Robotics; Human-Machine Interfaces, GUI Design, Computer Graphics; Programming Languages, Data Structures and Algorithms.

Research areas

Cognitive Computing and Systems, Adaptation and Learning, Data Mining and Knowledge Discovery, Approximate Reasoning and Decision Support; Intelligent Robotics, Autonomous Vehicles, Sensor Fusion, Medical Informatics.

Education

DipEng, National Polytechnic Institute of Grenoble, France, 1985
PhD, National Polytechnic Institute of Grenoble, France, 1989.
Master, National Polytechnic Institute of Grenoble, France, 1985.

Professional experience

Nanyang Technological University, Singapore, 1994-2009.
Sanyo Electric Research Laboratory, Japan, 1991–1993.
Electro-Technical Laboratory, AIST, Japan, 1989–1991.
Informatics and AI Laboratory, INRIA, France, 1986-1989.

Memberships

IEEE Computational Intelligence Society (CIS); IEEE Robotics and Automation Society (RAS); Institute of Electrical and Electronics Engineers (IEEE).

Contact

mpasquier@aus.edu
+971 6 515 2883

Dr. Michel Pasquier

Associate Professor
PhD in Computer Science, National Polytechnic Institute of Grenoble, France

Michel Pasquier has 15 years' experience teaching artificial intelligence and related CS courses at the Nanyang Technological University of Singapore. Previously, he was a researcher for the AIST and Sanyo Electric in Tsukuba, Japan. His research interests include cognitive computing and systems, adaptation and learning, knowledge discovery, as well as nature-inspired methods for approximate reasoning and decision making. He has published, led projects and served as a consultant in application areas including intelligent robotics and transportation systems, online learning, medical diagnosis and healthcare, and financial engineering.

Publications

A. Darwish and M. Pasquier (2013). Biometric identification using the dynamic features of the eyes. Proceedings of the IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS 2013), 1-6, Washington DC. DOI: 10.1109/ BTAS.2013.6712724
S. Ahmed, M. Pasquier, and G. Qadah (2013). Key issues in conducting sentiment analysis on Arabic social media text. Proceedings of the International Conference on Innovations in Information Technology (IIT 2013), 72–77, Abu Dhabi, UAE. DOI:10.1109/Innovations.2013.6544396
H. Huang, M. Pasquier, and C. Quek (2011). Decision support system based on hierarchical co-evolutionary fuzzy approach: A case study in detecting gamma ray signals. Expert Systems with Applications, 38(9): 10719-10729. DOI:10.1016/j.eswa.2010.10.011.
R.J. Oentaryo and M. Pasquier (2011). RFCMAC: A reduced rule-based localist neuro-fuzzy system for knowledge extraction. Expert Systems with Applications, 38(10): 12066-12084, DOI: 10.1016/j.eswa.2011.02.058.
R.J. Oentaryo and M. Pasquier (2011). Knowledge consolidation and inference in the integrated neuro-cognitive architecture. IEEE Intelligent Systems, 26(4): 62-71. DOI.:10.1109/MIS.2010.6.
I. Zualkernan, M. Pasquier, M. Jibreel, R.S. Zakaria, and R.M. Tayem (2010). An adaptive learning RPG game-engine based on knowledge spaces. Proceedings of the 2010 International Conference on Education Technology and Computer (ICETC 2010), 2:223–27, Shanghai. DOI:10.1109/ICETC.2010.5529397.
C. Quek, M. Pasquier, and B. Lim (2009). A novel self-organising fuzzy rule-based system for modelling traffic flow behaviour. Expert Systems with Applications, 47(4). DOI: 10.1016/j.eswa.2009.03.048.
H. Huang, M. Pasquier, and C. Quek (2009). Financial market trading system with a hierarchical co-evolutionary fuzzy predictive module. IEEE Transactions on Evolutionary Computation, Special issue on Computational Finance and Economics, 13(1): 56-70. DOI: 10.1109/ TEVC.2008.911682.
R.J. Oentaryo, M. Pasquier, and C. Quek (2008). GenSoFNN-Yager: A novel brain-inspired generic self-organizing neuro-fuzzy system realizing Yager inference. Expert Systems with Applications, 35(4): 1825-1840, 2008. DOI: 10.1016/j.eswa.2007.08.108.
M. Pasquier and R.J. Oentaryo (2008). Learning to drive the human way: A step towards intelligent vehicle. International Journal of Vehicle Autonomous Systems, Special Issue on Integrated Vehicle Control: Theories, Methods and Experimentation, 6(1/2): 24-47. DOI: 10.1504/ IJVAS.2008.016477.
C. Quek, M. Pasquier, and N. Kumar (2007). A novel recurrent neural network-based prediction system for option trading. International Journal of Applied Intelligence, Special Issue on Soft Computing Techniques Applied to Finance, 29(2): 138-151. DOI: 10.1007/s10489-007-0052-4.
C. Quek, M. Pasquier, and B. Lim (2006). POP-Traffic: A novel fuzzy-neural approach to road traffic analysis and prediction. IEEE Transactions on Intelligent Transportation Systems, 7(2): 133-146. DOI: 10.1109/ TITS.2006.874712.
K.T. Seow and M. Pasquier (2004). Supervising passenger land-transport systems. IEEE Transactions on Intelligent Transportation Systems, 5(3):165-176. DOI: 10.1109/ TITS.2004.833768.
K.K. Ang, C. Quek, and M. Pasquier (2003). POPFNN-CRI(S): A pseudo-outer product based fuzzy neural network using the compositional rule of inference and a singleton fuzzifier. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 33(6): 838-849. DOI: 10.1109/ TSMCB.2003.812850.
C. Quek and M. Pasquier (2002). POP-TRAFFIC: A novel fuzzy-neural approach to the modelling of traffic flow analysis and prediction. Intelligent Systems, Techniques and Applications, C.T. Leondes (ed.), CRC Press.
P.W. Ng, C. Quek, and M. Pasquier (2002). SPADES: Applying architectural patterns to the design of supervisory control systems. Intelligent Systems, Techniques and Applications, C.T. Leondes (ed.), CRC Press, 6: 1773-1829.
K.T. Seow and M. Pasquier (2002). Vehicle route-sequence planning using temporal logic. Inter-national Journal of Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AIEDAM), 16(1): 31-38. DOI: 10.1017/ S0890060401020042.
M. Pasquier, C. Quek, and M. Toh (2001). Fuzzylot: A novel self-organising fuzzy-neural rule-based pilot system for automated vehicles. Neural Networks Journal, 14(8): 1099-1112. DOI: 10.1016/ S0893-6080(01)00048-X.
M. Pasquier, C. Quek, B.T. Tan, and S. Chan (2001). Opportunistic planning for a fleet of transportation robots. Journal of Engineering Applications of Artificial Intelligence (EAAI), 14(3): 329-340. DOI: 10.1016/ S0952-1976(01)00010-0.
C. Quek, M. Pasquier, and P.W. Ng (1999). Structuring expert control using the integrated process supervision architecture. Expert Systems Techniques and Applications, C.T. Leondes (ed.), Breach International Series in Engineering, Technology and Applied Science.

Awards and Honors

Qualification "Professeur des Universites", National University Council, France, 2009.
Research Fellow Grant, Science and Technology Agency, Japan, 1990–1991.
Research Fellow Grant, Agency for Industrial Science and Technology, Japan, 1989–1990.
PhD Scholarship, Research Development Agency, France, 1986–1988.

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