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Call for Papers

The 2020 IEEE International Conference on Computational Electromagnetics (ICCEM 2020) will be held in Singapore, from 25 March to 27 March, 2020. ICCEM 2020 is and financially sponsored by IEEE Antennas and Propagation Society. It brings together researchers and practitioners for sharing their latest advances in numerical algorithms, modeling methods, optimization and animation tools, and computing platforms for applications across the whole electromagnetic spectrum.

Prospective authors are cordially invited to submit two-page papers or one-page abstract (the abstract must have at least 250 words) in all areas of simulation techniques, computational methods and/or focus on scientific and engineering applications. The following is a list of suggested topics. Contributions in other areas of computational electromagnetics and applications will also be considered.

The preliminary paper submission deadline is Tuesday, October 1, 2019.

The preliminary paper submission deadline has been extend to Sunday, October 20, 2019.

Download the pdf-version Call for Paper here

Computational Methods
Integral Equation
Differential Equation
Antenna Arrays
Hybrid and Multi-Physics
Domain Decomposition
EMC/EMI in Large Platform
EM Scattering and Inverse Scattering
Fast and Efficient Techniques
High Frequency Methods
RF and Microwave Circuits
EBG and Frequency Selective Surfaces
Transient Time Domain Analysis
Hybrid Time and Frequency Techniques
Metamaterial and Artificial Materials
Signal/Power Integrities in ICs and Packages
A Posteriori Error Estimate and Adaptive Mesh Refinements
Reduced Order Modeling
Fast CEM Modelling for 5G Communication
Nano-electronics and Nano-electromagnetics
Data Analytics
Data-Sparse Representation
Co-Simulation of Electronic Circuits
Fast CEM Modelling for Health Care
Simulation Techniques
High Performance Computing
Mesh Generation
Scientific Visualizations
Parallel and GPU Computations
Design & Optimization Techniques
User Interfaces
Computer Graphics
Emerging Areas
Artificial intelligence
machine learning and deep learning based computational electromagnetics methods
computational electromagnetic-acoustics
other relevant topics

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