People

PhDr. Nirupam Chakraborti

nirupam.chakraborti (at) fs.cvut.cz

room: A-325, Praha, Jugoslávských partyzánů

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• Journal papers
• Proceeding papers
• Book chapters
• Invited unpublished lecture

More informations available in external application. V3S.

Journal papers

2025

• Multi-Objective Optimization of Composite Kayak Paddle Shaft Through Evolutionary Deep Learning – Kropík, B.; Mareš, T.; Malá, A.; Doubrava, K.; Padovec, Z.; Fošnarič, M.; Chakraborti, N., Materials and Manufacturing Processes. 2025, 40(7), 893-901. ISSN 1532-2475.
• Analysis of Thermoelastic Stresses in Filament Wound Composite Pressure Vessels Using Evolutionary Deep Learning and Many-objective Optimisation – Vondráček, D.; Padovec, Z.; Mareš, T.; Chakraborti, N., Philosophical Magazine Letters. 2025, 105(1), 1-29. ISSN 1362-3036.

2024

• The stacking sequence optimisation of a filament wound composite bicycle frame using the data-driven evolutionary algorithm EvoDN2 – Malá, A.; Padovec, Z.; Mareš, T.; Chakraborti, N., Philosophical Magazine Letters. 2024, 104(1), 1-19. ISSN 1362-3036.
• Complex Design and Analysis of Filament Wound Composite Pressure Vessels Using Data Driven Evolutionary Algorithms – Vondráček, D.; Padovec, Z.; Mareš, T.; Chakraborti, N., Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. 2024, 1-10. ISSN 2041-3009.
• Analysis and Optimization of Junction between Cylindrical Part and End Dome of Filament Wound Pressure Vessels Using Data Driven Evolutionary Algorithms – Vondráček, D.; Padovec, Z.; Mareš, T.; Chakraborti, N., Proceedings of Institution of Mechanical Engineers Part C: Journal of Mechanical Engineering Science. 2024, 238(6), 2348-2361. ISSN 2041-2983.

2023

• Parameter estimation with the Markov Chain Monte Carlo method aided by evolutionary neural networks in a water hammer model – Carvalho, R.; Herzog, I.; Barreto Orlande, H.; Colaco, M.; Madeira, I.; Chakraborti, N., COMPUTATIONAL & APPLIED MATHEMATICS. 2023, 42(1), ISSN 2238-3603.
• Interactive data-driven multiobjective optimization of metallurgical properties of microalloyed steels using the DESDEO framework – Saini, B.; Chakrabarti, D.; Chakraborti, N.; Shavazipour, B.; Miettinen, K., Engineering Applications of Artificial Intelligence. 2023, 120 ISSN 0952-1976.
• Evolutionary data driven modeling and tri-objective optimization for noisy BOF steel making data – Mahanta, B.; Gupta, P.; Mohanty, I.; Roy, T.; Chakraborti, N., Digital chemical engineering. 2023, 7 ISSN 2772-5081.
• Evolutionary algorithms in robot calibration – Bastl, P.; Chakraborti, N.; Valášek, M., Materials and Manufacturing Processes. 2023, 38(16), 2051-2070. ISSN 1042-6914.
• A method for designing filament-wound composite frame structures using a data-driven evolutionary optimisation algorithm EvoDN2 – Malá, A.; Padovec, Z.; Mareš, T.; Chakraborti, N., Philosophical Magazine Letters. 2023, 103(1), 1-19. ISSN 0950-0839.
• Evolutionary multi-objective optimization of truss topology for additively manufactured components – David, P.; Mareš, T.; Chakraborti, N., Materials and Manufacturing Processes. 2023, 38(15), 1922-1931. ISSN 1042-6914.
• Optimization of Dome Shape for Filament Wound Pressure Vessels Using Data-Driven Evolutionary Algorithms – Vondráček, D.; Padovec, Z.; Mareš, T.; Chakraborti, N., Materials and Manufacturing Processes. 2023, 38(15), 1899-1910. ISSN 1042-6914.

Proceeding papers

2024

• Návrh a analýza navíjených kompozitních tlakových nádob s využitím datově řízených evolučních algoritmů – Vondráček, D.; Padovec, Z.; Mareš, T.; Chakraborti, N., In: Konference mechanika kompozitních materiálů a konstrukcí MK2. Praha: CTU FME. Department of Mechanics, Biomechanics and Mechatronics, 2024. p. 33-38. ISBN 978-80-01-07338-4.
• The Use of Data Driven Evolutionary Algorithms for Safe Design of Integrally Wound Composite Pressure Vessel – Padovec, Z.; Vondráček, D.; Mareš, T.; Chakraborti, N., In: 25th International Scientific Conference APPLIED MECHANICS 2024 AM 2024 BOOK OF ARTICLES. Žilina: University of Žilina, 2024. p. 114-119. ISBN 978-80-554-2090-5.

2023

• Evolutionary multi-objective optimization of truss topology for additively manufactured components – David, P.; Mareš, T.; Chakraborti, N., In: KomPlasTech 2023 - extended abstracts. Krakow: Academica, 2023.
• Dome Shape Optimization of Composite Pressure Vessels Using Data-Driven Evolutionary Algorithms – Vondráček, D.; Padovec, Z.; Mareš, T.; Chakraborti, N., In: KomPlasTech 2023 - extended abstracts. Krakow: Academica, 2023.

Book chapters

2024

• Shallow and Deep Evolutionary Neural Networks Applications in Solid Mechanics – Malá, A.; Padovec, Z.; Mareš, T.; Chakraborti, N., In: Advanced Machine Learning with Evolutionary and Metaheuristic Techniques. Springer Nature Singapore Pte Ltd., 2024. p. 257-296. ISSN 2510-1765. ISBN 978-981-99-9717-6.

Invited unpublished lecture

2023

• Výpočetní metody a optimalizace navíjených kompozitních tlakových nádob – Padovec, Z.; Vondráček, D.; Mareš, T.; Chakraborti, N., [Invited unpublished scientific lecture] Praha: Seminář Kompozity v Energetice, Česká společnost pro mechaniku. 2023-11-23.