Dr George Panoutsos
Director of Learning and Teaching
Reader in Computational Intelligence
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
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'. Dr Panoutsos leads the Human-Centric Systems laboratory, currently with four research students and one post-doctoral researcher.
- 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
- ACS133, Physical Systems (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
- Baraka A, Panoutsos G & Cater S (2015) A real-time quality monitoring framework for steel friction stir welding using computational intelligence. Journal of Manufacturing Processes, 20(P1), 137-148.
- Zhang Q, Mahfouf M, Panoutsos G, Beamish K & Liu X (2015) Multiobjective optimal design of friction stir welding considering quality and cost issues. Science and Technology of Welding and Joining, 20(7), 607-615. View this article in WRRO
- De Alejandro Montalvo J, Panoutsos G, Mahfouf M & Catto JW (2015) High Dimensionality and Scaling-up Performance of RBF Models with Application to Healthcare Informatics. International Journal of Machine Learning and Computing, 5(1), 62-67.
- Solis AR & Panoutsos G (2014) Interval Type-2 Radial Basis Function Neural Network: A Modeling Framework. IEEE Transactions on Fuzzy Systems, 23(2), 457-473.
- Solis AR & Panoutsos G (2013) Granular computing neural-fuzzy modelling: A neutrosophic approach. APPLIED SOFT COMPUTING, 13(9), 4010-4021.
- Zhang Q, Mahfouf M, Panoutsos G, Beamish K & Norris I (2012) Knowledge discovery for friction stir welding via data driven approaches Part 2 - Multiobjective modelling using fuzzy rule based systems. Science and Technology of Welding and Joining, 17(8), 681-693.
- Samuri SM, Panoutsos G, Mahfouf M, Mills GH, Denaï M & Brown BH (2011) Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT). Communications in Computer and Information Science, 273, 191-204.
- Zhang Q, Mahfouf M, Yates JR, Pinna C, Panoutsos G, Boumaiza S, Greene RJ & de Leon L (2011) Modeling and Optimal Design of Machining-Induced Residual Stresses in Aluminium Alloys Using a Fast Hierarchical Multiobjective Optimization Algorithm. Materials and Manufacturing Processes, 26(3), 508-520.
- Panoutsos G & Mahfouf M (2010) A neural-fuzzy modelling framework based on granular computing: Concepts and applications. Fuzzy Sets and Systems, 161(21), 2808-2830.
Conference proceedings papers
- Baraka A, Panoutsos G & Cater S (2016) Perpetual Learning Framework based on Type-2 Fuzzy Logic System for a Complex Manufacturing Process. IFAC-PapersOnLine, Vol. 49(20) (pp 143-148) View this article in WRRO
- Solis AR & Panoutsos G (2016) Iterative Information Granulation for Novelty Detection in Complex Datasets. 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 24 July 2016 - 29 July 2016. View this article in WRRO
- Tzagarakis G & Panoutsos G (2016) Model-Based Feature Selection Based on Radial Basis Functions and Information Measures. 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 24 July 2016 - 29 July 2016. View this article in WRRO
- Gonzalez-Rodriguez A, Panoutsos G, Mahfouf M & Beamish K (2014) A Novelty detection framework based on fuzzy entropy for a complex manufacturing process. IEEE International Conference on Intelligent Systems 2014, IEEE IS'14. Warsaw, Poland, 24 September 2014 - 26 September 2014.
- Baraka A, Panoutsos G, Mahfouf M & Cater S (2014) A Shannon Entropy-Based Conflict Measure For Enhancing Granular Computing-Based Information. The 2014 IEEE International Conference on Granular Computing. Noboribetsu, Hokkaido, Japan, 22 October 2014 - 24 October 2014.
- Solis, A.R. & Panoutsos G (2014) Fuzzy uncertainty assessment in RBF Neural Networks using neutrosophic sets for multiclass classification. IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014. Beijing, China, 6 July 2014 - 11 July 2014.
- Solis AR, Thornton S & Panoutsos G () Data-driven Fuzzy Modelling Framework for Classification of Imbalanced Data. Proceedings of the IEEE 9th International Conference on Intelligent Systems (pp 302-307), 4 September 2016 - 6 September 2016.