Dr George Panoutsos

Director of Learning and Teaching
Senior Lecturer

George P Image 198x234Address:
Dr George Panoutsos BEng(Hons), MSc, PhD, MIET, MIEE
Department of Automatic Control and Systems Engineering
University of Sheffield
Sheffield, S1 3JD
Tel: (+44) (0)114 222 5130
Fax: (+44) (0)114 222 5683
Email: g.panoutsos@sheffield.ac.uk
Room: C6a, Amy Johnson Building


Biopic
Research Interests
Professional activities and recognition
Current Teaching and Administration
Selected Publications since 2007

Biopic

Dr George Panoutsos is a postgraduate of the department having completed the M.Sc. course in Automatic Control and Systems Engineering in 2003. He obtained his Ph.D. degree in 2007 after studying Computational Intelligence modelling in the Intelligent Systems Research Group of the department. His research work led to a number of international journal publications and an international patent in the field of Granular Computing.

Dr Panoutsos is currently a Member of the IMMPETUS Research Group working in the areas of metals design and processing with applications focusing on 'through-process modelling and optimisation' as well as 'prediction of mechanical properties' and real-time monitoring' using data-driven methodologies. He has also been working in the fields of Bioengineering and Healthcare and is currently a Member of the Intelligent Systems Research Laboratory, with projects involving 'automation in the care of the critically ill in the Intensive Care Unit' and 'cancer prediction using clinical and gene data'. Following his appointment as a Lecturer in the department, Dr Panoutsos  leads the Human-Centric Systems laboratory, currently with four research students and one post-doctoral researcher.

Research Interests

  • Human-Centric Systems
  • Computational Intelligence (CI) and Artificial Intelligence (AI)
  • Granular Computing (GrC) and Computing with Words
  • Biologically inspired computing and optimisation
  • Incremental learning – Smart Adaptive Systems
  • Data mining, classification and information fusion
  • Biomedical intelligent systems and Decision Support in healthcare
    • Hybrid gene-clinical based prediction of cancer
    • Decision support and modelling for the Intensive Care Unit
    • absolute Electrical Tomography Imaging (aEIT) for lung ventilation
    • Therapy outcome prediction: Early Adjacent Segment Disease (EASD)
  • Systems engineering approach to modelling and optimisation for the thermomechanical processing of metals
    • Mechanical properties of aerospace materials
    • Multiscale characterisation of critical components
    • Real-time process monitoring and non-destructive model-based evaluation

Recent research awards and projects as a PI

  • EU H2020, Factories of The Future - 01: Process Optimisation of Manufacturing Assets, COMBILASER, (co-I and academic lead, £3.48M, Jan.2015 - Jan.2018)
  • TSB, Sustained Process Excellence through Embedding of Analytics and Knowledge Management into Process Chains (in collaboration with TATA Steel Long Products Europe and K-Now, Academic PI, total project cost £441,118 Sep.2014 - Mar.2016)
  • EPSRC/Sheffield University (PI £61,226) Model-based performance evaluation for critical manufacturing processes 1/2012-6/2012
  • TWI Ltd. Yorkshire, UK (PI £29,000) Automated Systems for Intelligent Stir Tracking and Optimisation, 2012-2014
  • TWI Ltd. Cambridge, UK (PI £6,000) Multiscale model-based search for optimal Process Operating Windows in Friction Stir Welding, 2010-2013
  • METRC Innovation Award (PI £10,000) Online and real-time condition monitoring of Friction Stir Welding 01/01/2013 – 31/12/2014

Current Teaching and Administration

  • ACS125, Systems Modelling and Simulation (joint module leader)
  • ACS6101, Foundations of Control Systems (Systems Modelling and Simulation)
  • FCE101, Introduction to Bioengineering (Medical Devices and Systems)
  • Bioengineering degree Board of Studies
  • Bioengineering degree, theme leader: Medical Devices and Systems
  • Director of admissions, UG Bioengineering studies
  • MSc in Advanced Manufacturing, Board of Studies (ACSE Representative)

Professional activities and recognition

  • Member of the IMMPETUS management committee (The Institute of Microstructural and Mechanical Process Engineering: The University of Sheffield)
  • Member of INSIGNEO, Institute for in silico medicine, Sheffield University
  • Member of the IET
  • Member of the IEEE
  • IPC member of several international conferences (e.g. IEEE IS 2010 (IPC and session chair), IEEE GrC 2010 and 2011, ICNC’10, BIOSTEC Biosignals 2011, BIOSTEC Bioinformatics)
  • Referee for a number of international journals and conferences

Selected Publications

A. Gonzalez-Rodriguez, G. Panoutsos, M. Mahfouf and K. Beamish, A Novelty detection framework based on fuzzy entropy for a complex manufacturing process, IEEE IS’2014, International Conference on Intelligent Systems, Warsaw, Poland, September 24-26, 2014 (2014)

A.R. Solis and G. Panoutsos, Fuzzy uncertainty assessment in RBF Neural Networks using neutrosophic sets for multiclass classification, FUZZ-IEEE 2014, IEEE International Conference on Fuzzy Systems and IEEE World Congress on Computational Intelligence (WCCI), July 6-11, Beijing, China (2014)

A.R. Solis and G. Panoutsos, Interval Type-2 Radial Basis Function Neural Network:
A Modelling Framework, IEEE Trans. on Fuzzy Systems, (in press 2014)
http://dx.doi.org/10.1109/TFUZZ.2014.2315656

A.R. Solis and G. Panoutsos, Granular Computing Neural-Fuzzy Modelling:
A Neutrosophic Approach, Applied Soft Computing, 13(9), pp. 4010-4021, 2013
http://dx.doi.org/10.1016/j.asoc.2012.09.002

S. M. Samuri, G. Panoutsos, M. Mahfouf, G. H. Mills, M. Denai and B. H. Brown, Towards a patient-specific model of lung volume using absolute Electrical Impedance Tomography (aEIT), Biomedical Engineering Systems
and Technologies, Communications in Computer and Information Science Volume 273, pp 191-204 (2013)
(http://dx.doi.org/10.1007/978-3-642-29752-6_14)

Q. Zhang, M. Mahfouf, G. Panoutsos, K. Beamish and I. Norris, Knowledge Discovery for Friction Stir Welding via Data-driven Approaches - Part 1: Correlation Analyses of Internal Process Variables and Weld Quality,
Science and Technology of Welding and Joining, 17(8), pp. 672-680, 2012
(http://dx.doi.org/10.1179/1362171812Y.0000000061)

Q. Zhang, M. Mahfouf, J. R. Yates, C. Pinna, G. Panoutsos, S. Boumaiza, R. J. Greene, L. de Leon, Modelling and optimal design of machining induced residual stresses in aluminium alloys using a fast hierarchical
multi-objective optimisation algorithm, Materials and Manufacturing Processes, 26(3), pp. 508-520,
2011 (http://dx.doi.org/10.1080/10426914.2010.537421)

Q. Zhang, M. Mahfouf, G. Panoutsos, K. Beamish and I. Norris, Knowledge Discovery for Friction Stir Welding via Data-driven Approaches - Part 2: Multi-objective Modelling using Fuzzy Rule-based Systems, Science and
Technology of Welding and Joining, 17(8), pp. 681-693, 2012
http://dx.doi.org/10.1179/1362171812Y.0000000062

G. Panoutsos and M. Mahfouf, "Neural-Fuzzy Modelling Framework Based on Granular Computing: Concepts and Applications", Fuzzy Sets and Systems, 161(21), pp.2808-2830, 2010
(http://dx.doi.org/10.1016/j.fss.2010.06.004)

C. H. Ting, M. Mahfouf, A. Nassef, D. A. Linkens, G. Panoutsos, P. Nickel, A. C. Roberts and G. R.J. Hockey, "Real-time adaptive automation system based on identification of operator functional state (OFS) in simulated process control operations", IEEE Transactions on Systems, Man and Cybernetics-Part A: Systems and Humans 40(2), pp. 251-262, 2010
(http://dx.doi.org/10.1109/TSMCA.2009.2035301)

M. Denai, M. Mahfouf, S .Mohamad-Samuri, G. Panoutsos, B.H. Brown and G.H. Mills, "Absolute Electrical Impedance Tomography (aEIT) Guided Ventilation Therapy in Critical Care Patients: Simulations and
Future Trends", IEEE Transactions on Information Technology in Biomedicine, 14(3) pp. 641-649, 2010
(http://dx.doi.org/10.1109/TITB.2009.2036010)

A. Wang, M. Mahfouf, G. H. Mills, G. Panoutsos, D. A. Linkens, K. Goode, H.F. Kwok, M. Denai, "Intelligent Model-Based Advisory System for the Management of Ventilated Intensive Care Patients: Hybrid Blood Gas
Patient Model", /Computer Methods and Programs in Biomedicine, Elsevier/, 99(2), pp. 195-207, 2010
(http://dx.doi.org/10.1016/j.cmpb.2009.09.011)

A. Wang, M. Mahfouf, G. H. Mills, G. Panoutsos, D. A. Linkens, K. Goode, H.F. Kwok, M. Denai, “Intelligent Model-Based Advisory System for the Management of Ventilated Intensive Care Patients - Part II: Advisory
System Design and Evaluation”, Computer Methods and Programs in Biomedicine, Elsevier, 99(2), pp. 208-217, 2010
(http://dx.doi.org/10.1016/j.cmpb.2010.03.009)

G. Panoutsos and M. Mahfouf, "An incremental learning structure using granular computing and model fusion with application to materials processing", /Studies in Computational Intelligence (SCI), Intelligent
Techniques and Tools for Novel System Architectures, Springer Berlin / Heidelberg/, 109, pp.139-153, 2008
(http://dx.doi.org/10.1007/978-3-540-77623-9_8)