The 3rd International Conference on Data-Driven Computing and Machine Learning in Engineering 2023 will be held in Beijing during Jul. 23-25, 2023.
In the age of big data, machine learning technology has been effectively utilized in various fields such as image processing, genomics, engineering computing, macroeconomic forecasting, and medical diagnosis. However, despite its success, applying data-driven computing and machine learning in engineering analytics still presents several unresolved challenges. With the aim of promoting research and the application of big data analysis, data-driven computing, and artificial intelligence in engineering, as well as fostering scientific exchanges among scientists, practitioners and engineers from related disciplines, the International Conference on Data-Driven Computing and Machine Learning in Engineering (DACOMA) has been held annually since 2019. Due to the pandemic, the second DACOMA conference was postponed to 2022. The first DACOMA conference was held in 2019 in Shanghai, China and was organized by Tongji University, with renowned computational mechanics scholars Academician Hehua Zhu and Academician Timon Rabczuk (European Academy of Sciences) as its chairs. The 2nd DACOMA conference was successfully concluded in 2022 in Beijing, China. The conference will be hosted by Beijing Institute of Technology and the Chinese Society of Theoretical and Applied Mechanics, with Professor Pengwan Chen, Professor Zhanli Liu, and Professor Xiaoying Zhuang, prominent scholars in the field of computational mechanics, serving as the conference chairs. This year's conference will continue to focus on machine learning-related topics.
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2023.0916Program Book Download Here!Download the program book here.
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2023.0815DACOMA2023 - Prof. Klaus-Jürgen Bathe online presentation
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2023.0803第三届工程中的数据驱动计算和机器学习国际会议通知第三届工程中的数据驱动计算和机器学习国际会议通知.pdf
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● 1.Image reconstruction of materials based on machine learning
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● 2.Constitutive models based on data-driven
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● 3.Solution of PDEs based on machine learning
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● 4.Design and optimization of big data
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● 5.Uncertainty analysis of geomechanical models
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● 6.Machine learning for material characterization
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● 7.Simulation techniques of data-driven
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● 8.Processing of high-performance data
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● 9.Data-driven technology in multiscale and multi-field simulations
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● 10.Visualization and visual analysis of multi-source data
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● 11.Data-driven techniques for continuous and discrete methods
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● 12.Dynamic data-driven computing
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● 13.Design of metamaterials and advanced materials based on machine learning
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20th July 2023:Deadline for final registration and payment
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23rd July 2023:Reception
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24th-25th July 2023:Day of the conference