Big data and smart computing are emerging research fields that have been drawing much attention from diverse disciplines including computer science, information technology, and social sciences. The goal of the International Conference on Big Data and Smart Computing (BigComp), initiated by KIISE (Korean Institute of Information Scientists and Engineers), is to provide an international forum for exchanging ideas and information on current studies, challenges, research results, system developments, and practical experiences in these emerging fields among researchers, developers, and users from academia, business and industry. Following the successes of the previous BigComp conferences in Bangkok, Thailand (2014), Jeju, Korea (2015), Hong Kong, China (2016), Jeju, Korea (2017), Shanghai, China (2018), Kyoto, Japan (2019), Busan, Korea (2020), Jeju, Korea (2021), Daegu, Korea (2022), and Jeju, Korea (2023), the 2024 IEEE International Conference on Big Data and Smart Computing (IEEE BigComp 2024) will be held in Bangkok, Thailand. The conference is co-sponsored by IEEE and KIISE. IEEE BigComp 2024 invites authors to submit original research papers and as well original work-in-progress reports on big data and smart computing.
BigComp 2024 will be held in Bangkok, Thailand. Bangkok is the capital and most populous city of Thailand. It is a center for business, finance, and tourism. It is a popular tourist destination for its historical landmarks, temples, palaces, and vibrant nightlife. The Sukosol Hotel, the conference venue, is close to many popular tourist attractions, including the Grand Palace, Wat Pho, and the Chatuchak Weekend Market.
General Co-Chairs
• Herwig Unger (University of Hagen, Germany)
• Jinseok Chae (Incheon National University, Korea)
Organization Chair
• Phayung Meesad (King Mongkut’s University of Technology North Bangkok, Thailand)
Program Committee Co-Chairs
• Christian Wagner (University of Nottingham, U.K.)
• Chaokun Wang (Tsinghua University, China)
• Mehdi Bennis (University of Oulu, Finland)
• Young-Koo Lee (Kyunghee University, Korea)
Workshop Co-Chairs
• Mahasak Ketcham (King Mongkut’s University of Technology North Bangkok, Thailand)
• Young-Kyoon Suh (Kyungpook National University, Korea)
Tutorial Co-Chairs
• Mario Kubek (Georgia State University, USA)
• Noseong Park (Yonsei University, Korea)
Finance Chair
• Joonho Kwon (Pusan National University, Korea)
Publication Chair
• Hyuk-Yoon Kwon (Seoul National University of Science and Technology, Korea)
Poster Session Chair
• Suan Lee (Semyung University, Korea)
We invite the submission of original research contributions in the following areas, but also welcome any original contributions that may cross the boundaries among areas or point in other novel directions. In addition, BigComp 2024 encourages submissions about products, practices, and services in industry:
• Big data analytics and social media
• Big data applications / big data as a service
• Big data ecosystem
• Bioinformatics, multimedia, smartphones, etc.
• Cloud and grid computing for big data
• Crowdsourcing and human-in-the-loop
• Data mining and data science
• Data and information quality
• Disaster analysis
• Infrastructure and platform for big data and smart computing
• Knowledge graph, graph data management and mining
• Machine learning and AI for big data
• Machine learning and AI theory and fundamentals
• Mobile communications and smart location-based services
• Recommender systems
• Search/retrieval and generation of big data
• Security and privacy for big data
• Smart computing models, tools, and devices
• Techniques, models and algorithms for big data
• Tools and systems for big data
• Understanding multi-modal data
Feb 18
2024
Feb 21
2024
Draft paper submission deadline
Draft Paper Acceptance Notification
Registration deadline
2023-02-13 South Korea Jeju
2023 IEEE International Conference on Big Data and Smart Computing2019-02-27 Japan
2019 IEEE International Conference on Big Data and Smart Computing2018-01-15 China
2018 IEEE International Conference on Big Data and Smart Computing
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