Specialty
mechanics (mechanics, computational methods, methods of artificial intelligence, multi-scale modeling)

Scientific activity

• PhD degree in Mechanical Engineering obtained in 2002,
• habilitated doctor of technical sciences in mechanics in 2012.  

Research interests
The main area of research interest is related to the application of parallel artificial intelligence methods in multiscale optimization problems. Computations are conducted using methods such as parallel, distributed, grid evolutionary algorithms, artificial immune systems, swarms systems. Multiscale issues are solved on the basis of the numerical homogenization method and direct methods in different scales using the finite element method (FEM) or boundary element method (BEM). Parallelization of calculations are carried out hierarchically using three levels: optimization algorithm, homogenization methods and direct problem solving using FEM or BEM. The calculations are carried out on multicore processors, multiprocessor systems, the GPU cards as well as clusters and supercomputers.

The most important published works, among others:

• Operational Load Monitoring of a Composite Panel Using Artificial Neural Networks, W. Mucha, W. Kuś, J. C. Viana, J. P. Nunes, Sensors, 20, 2534, 2020, https://doi.org/10.3390/s20092534
• Mechanical Properties of Monolayer MoS2 with Randomly Distributed Defects, M. J. Akhter, W. Kuś, A. Mrozek, T. Burczyński, Materials, 13(6), 1307, 2020, https://doi.org/10.3390/ma13061307
• Burczynski, T., Kuś, W., Beluch, W., Długosz, A., Poteralski, A., Szczepanik, M., Intelligent Computing in Optimal Design , Solid Mechanics and Its Applications, Series Volume 261, Springer International Publishing 2020. https://doi.org/10.1007/978-3-030-34161-9
• Anisotropic-Cyclicgraphene: A New Two-Dimensional Semiconducting Carbon Allotrope. M. Maździarz, A. Mrozek, W. Kuś, T. Burczyński, Materials, 11(3), 432, 2018, doi:10.3390/ma11030432
• Application of mode superposition to hybrid simulation using real time finite element method, W. Mucha, W. Kuś, MECHANIKA, 23(5), pp.673-677, 2017, http://dx.doi.org/10.5755/j01.mech.23.5.14642
• FPGA support in hybrid simulation using finite element method, W. Mucha, W. Kuś, Solid State Phenomena , 260 SSP, pp. 105-112, 2017, DOI: 10.4028/www.scientific.net/SSP.260.105
• Method for determining structures of new carbon-based 2D materials with predefined mechanical properties, A. Mrozek, W. Kuś, T. Burczyński, International Journal for Multiscale Computational Engineering, 2017, DOI: 10.1615/IntJMultCompEng.2017020429
• First-principles study of new X-graphene and Y-graphene polymorphs generated by the two stage strategy, M. Maździarz, A. Mrozek, W. Kuś, T. Burczyński, Materials Chemistry and Physics, 202C, 7-14, 2017, DOI: 10.1016/j.matchemphys.2017.08.066
• Multicriteria identification of parameters in microscale heat transfer, W. Kuś, J. Dziatkiewicz, International Journal of Numerical Methods For Heat & Fluid Flow, 27(3), 587-597, 2017, DOI: 10.1108/HFF-03-2016-0109
• CFD-based shape optimisation of a CO2 two-phase ejector mixing section, M. Palacz, J. Smolka, W. Kuś, et al., Applied Thermal Engineering, 95, 62-69, 2016, DOI: 10.1016/j.applthermaleng.2015.11.012
• Nano level optimization of graphene allotropes by means of a hybrid parallel evolutionary algorithm, A. Mrozek,W. Kuś, T. Burczyński, Computational Materials Science, Vol.106, 2015, pp. 161–169, doi:10.1016/j.commatsci.2015.05.002
• Memetic Optimization of Graphene-Like Materials on Intel PHI Coprocessor, W. Kuś, A. Mrozek, T. Burczynski, Artificial Intelligence and Soft Computing, Icaisc 2016, 9692, 401-410, 2016
• Optimization of bone scaffold structures using experimental and numerical data, P. Makowski, W. Kuś, Acta Mechanica, 227(1), 139-149, 2016
• Mode superposition and real time finite element method in hybrid simulation, W. Mucha, W. Kuś, Mechanika 2016: Proceedings of the 21st International Scientific Conference, 190-192, 2016
• Grid-enabled evolutionary algorithm application in the mechanical optimization problems, Kus, W., Engineering Applications of Artificial Intelligence, 20, 5, pp. 629-636, 2007. DOI: 10.1016/j.engappai.2006.11.018
• Bioinspired Algorithms in Multiscale Optimization, Kus, W.; Burczynski, T., Computer Methods in Mechanics, pp. 183-192, Springer, 2010.
• Optimization and defect identification using distributed evolutionary algorithms, Burczynski, T.; Kus, W.; Dlugosz, A.; et al., Engineering Applications of Artificial Intelligence, 17, 4, pp. 337-344, 2004. DOI: 10.1016/j.engappai.2004.04.007
• A computational continuum-discrete model of materials, Burczynski, T.; Mrozek, A.; Kus, W., Bulletin of the Polish Academy of Sciences-Technical Sciences, 55, 1, pp. 85-89, 2007.
• Microstructure Optimization and Identification in Multi-scale Modelling, Burczynski, T.; Kus, W., Eccomas Multidisciplinary Jubilee Symposium, 14, pp. 169-181, 2009.
• Parallel bioinspired algorithms in optimization of structures, Kus, W.; Burczynski, T., Parallel Processing and Applied Mathematics LNCS, 4967, pp. 1285-1292, 2008.

Organizational activities

• Head of Department of Methods of Artificial Intelligence and Applied Informatics in 2012-2013
• Deputy Director of the Institute of Mechanics and Computational Engineering for Research 2013 - current

Prizes, awards, membership in academic associations, among others:

• Member of ISSMO since 2009
• Member of PACM since 2002
• Member of AIAA since 2013
• Associate Member of Section of the Computational Methods and Optimization, Committee of Mechanics, Polish Academy of Sciences
• Associate Member of Section of the Section of Mechanics of Materials Mechanics, Committee of Mechanics, Polish Academy of Sciences
• FP7 reviewer