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ABAD 2023 : Applied Sciences: Advances in Deep Learning-Based Information Processing for Big Data Analytics and Digital Transformation


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Submission Deadline TBD

Call For Papers

Dear Colleagues,

Digitalization brings tremendous opportunities and unprecedented challenges to humanity. It constantly transforms our understanding of our world, the way we interact with each other, as well as the way the world itself operates. Data and analytics are key to digital transformation. With the recent advances in Artificial intelligence and Machine learning, we are starting to move into the phase where we can automate to make use of these vast amounts of data generated every day. Deep learning technologies had been revolutionary in learning from structured and unstructured data; however, constant innovations and research in this direction would ensure higher reliability and more comprehensibility into the domain.

This Special Issue calls for the latest research contributions in the area of big data analytics and digital transformation facilitated by deep-learning-based neural information processing. In this issue, contributions could cover state-of-the-art deep learning techniques for addressing big data; novel approaches for adapting deep learning for applications in other fields; innovative methods to address digital transformation through machine learning; the brilliant ideas to address challenges and identify possible solutions using big data analytics; and the new concepts that potentially lead to disruptive technological and societal innovation through digital transformation.

The articles of this Special Issue will contribute to natural sciences and engineering facilitated by computer sciences such as artificial intelligence, data analytics, machine learning, pattern recognition, big data manipulation, data fusion, as well as digital twin technologies in various applications. The scope of the expected contributions is also extended to social sciences with data-driven approaches applied to economics, business, finance, management, and sociology in order to analyze complex resources for better decision making, collaboration, and value creation.

Prof. Dr. Xiao Chen
Prof. Dr. ASM Shihavuddin
Prof. Dr. Dan Zheng
Guest Editors

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