Machine Learning - CfP: Emerging Applications and Frontiers for Data Science (DSAA 2023 journal track)
Emerging Applications and Frontiers for Data Science (DSAA 2023 journal track)
Data science is a classic topic with an extensive scope, both in terms of theory and applications. Machine learning has been gaining ever-increasing importance in providing with innovative solutions and methodologies to data science tasks. The recent years have witnessed the booming of a number of emerging frontiers in machine learning including large language models, AIGC and trust-aware learning, which are bound to exert profound impact on data science in general. This special issue will therefore highlight the latest development of the Machine learning foundations of data science and on the synergy of data science and machine learning. We welcome new developments in statistics, mathematics, informatics and computing-driven machine learning for data science, including foundations, algorithms and models, systems, innovative applications and other research contributions. In particular, we give priority to research efforts bringing new problems and challenges, using new tools to address classic problems, and expanding the application of known techniques to new domains and settings, in the general context of data science.
We look for research work exploring answers to the important questions like the following:
What are the challenges and the opportunities brought by the recent advances in machine learning, such as generative AI, Large Language Model, etc.? What are the new techniques and solutions introduced in data science and analytics by these advances in machine learning? How would these emerging topics advance data analytics, for example, in the detection of data integrity, fraud, anomaly, change, event and crisis？ How can the advanced data science and analytics methods be used to solve the data ethical issues raised by these emerging domains such as generative AI? How can the generative AI be used to help define a suitable setup for some data analytics experiments? How can the advanced language models help interpret the results of statistical analysis? How can the advanced language models help on decision-making, advanced personalized search and recommendation?
While we look for submissions addressing the above-mentioned questions, following the great success of the 2021 and 2022 MLJ special issue with DSAA'2021 and DSAA’2022, this 2023 special issue will also capture the state-of-the-art machine learning advances for data science including but not limited to the following topics:
- Deep learning (theory, architectures, reinforcement learning, generative models, optimization for neural networks, …)
- AI generation (image, music, video, 3D, etc.) that support, challenge and provoke human creativity
- Data ethical issues (including appropriation, authorship, etc.) raised by creative AI
- Methodologies for the evaluation of artefacts created with creative AI
- Emerging applications based on large-scale language model (LLM) AI and learning from multimodal data
- Human-AI collaboration and human-centered AI
- Data preprocessing, manipulation and augmentation
- Data integrity, security and fault tolerance
- Data science for decision support systems, marketing, online and e-commerce
- Visualization of data, models and predictions Pattern recognition, predictive modelling and intelligent systems IoT, smart city, smart home, telecommunications, 5G and mobile data science and learning
- Government and enterprise data science
- Cybersecurity and information disorder, misinformation/fake detection
- Digital, social, economic and financial (finance, FinTech, blockchains and cryptocurrencies) analytics
- Frontiers AI applications (in digital twins, industry, healthcare, automotive, financial services, manufacturing, agriculture, and other areas)
- AI for science
Accepted papers will be published in MLJ and presented at a journal track of the 2023 IEEE International Conference on Data Science and Advanced Analytics (DSAA'2023) with a two-page abstract.
Schedule:
We will have a continuous submission/review process, submissions with revision which cannot be finalized before camera-ready deadline will be cycled to the next year’s DSAA.
Paper submission deadline: April 15, 2023
Paper acceptance: 1 July 2023
Camera-ready: 15 July 2023
Lead Guest Editor: Bingxue Zhang, University of Shanghai for Science and Technology, zhangbingxue@usst.edu.cn (this opens in a new tab)
Other Guest Editors:
Feida Zhu, Singapore Management University, Singapore, fdzhu@smu.edu.sg (this opens in a new tab)
Bin Yang, Aalborg University, Denmark byang@cs.aau.dk (this opens in a new tab)
João Gama, University of Porto, Portugal, jgama@fep.up.pt (this opens in a new tab)