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Americo CUNHA JR
39
Documents
Identifiants chercheurs
- americo-cunha-jr
- ResearcherId : D-5261-2009
- 0000-0002-8342-0363
- Google Scholar : http://scholar.google.com/citations?user=4r36RpoAAAAJ&hl=en
- IdRef : 253121612
Présentation
**Associate Professor of Applied Mathematics**
**[Rio de Janeiro State University - UERJ](http://www.uerj.br)**
The focus of our research group is directed to the interplay between mathematics, engineering, physics, and computational sciences, seeking to solve complex interdisciplinary problems in engineering and applied sciences. We are interested in both, basic research and applications, with special attention to the following topics:
- **Nonlinear Dynamics**
- **Uncertainty Quantification**
- **Inverse Problems**
- **Reduced Order/Surrogate Modeling**
- **Computational Science and Engineering**
- **Industrial Mathematics**
We work mainly in the qualitative and quantitative study of nonlinear phenomena and systems (epidemiological forecasting, damage detection, energy harvesters, etc.), seeking to better understand their underlying dynamic behavior. For this purpose we make use of sophisticated analytical, numerical and data-driven techniques, as well as hybrid approaches combining them. We are also interested in the development of state of art computational tools for the analysis of complex systems, such as numerical codes for ordinary/partial differential equations, reduced order/surrogate models, machine learning/statistical regressors, etc. In this context, our work is organized into the following interdisciplinary and transversal lines of research:
- **Nonlinear and chaotic phenomena in complex systems**
- **Probabilistic modeling of uncertainties in nonlinear systems**
- **Inverse problems for calibration of computational models**
- **Reduction of **complexity in** high order computational models**
- **Computational modeling of industrial problems**
More information: [www.americocunha.org](http://www.americocunha.org)
Publications
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Inference of nonlinear dynamical systems from data using sparse regression14th World Conference on Computational Mechanics, Jan 2021, Paris, France
Communication dans un congrès
hal-03109699v1
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Evolution equations for an epidemic via sparse regressionEBDS 2021 - Terceiro Encontro Brasileiro de Data Science, Aug 2021, São Paulo, Brazil
Communication dans un congrès
hal-03321689v1
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EPIDEMIC: a didactic tool for teaching mathematical epidemiologyXL Congresso Nacional de Matemática Aplicada e Computacional (CNMAC 2021), Sep 2021, Campo Grande (virtual), Brazil
Communication dans un congrès
hal-03338666v1
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EPIDEMIC: An educational code for teaching mathematical epidemiologyII Encontro Fluminense de Mulheres em Biomatemática, Nov 2020, Rio de Janeiro, Brazil
Communication dans un congrès
hal-03011145v1
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Employing 0-1 test for chaos to characterize the chaotic dynamics of a generalized Gauss iterated mapXIV Conferência Brasileira de Dinâmica, Controle e Aplicações (DINCON 2019), Nov 2019, São Carlos, Brazil
Communication dans un congrès
hal-02388470v1
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Inference of dynamical systems evolution laws from raw dataXIV Conferência Brasileira de Dinâmica, Controle e Aplicações (DINCON 2019), Nov 2019, São Carlos, Brazil
Communication dans un congrès
hal-02388475v1
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A data-driven approach for inference of the evolution equation of a Duffing oscillator15th International Conference on Vibration Engineering and Technology of Machinery (VETOMAC 2019), Nov 2019, Curitiba, Brazil
Communication dans un congrès
hal-02388469v1
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