Call for Papers: IEEE JSTSP Special Series on AI in Signal & Data Science - Toward Explainable, Reliable, and Sustainable Machine Learning

To address rapidly growing interest in artificial intelligence (AI) and machine learning (ML) for signal processing and data science, the IEEE Signal Processing Society (SPS) is launching a new special series on AI in Signal & Data Science, to be published within the IEEE Journal on Selected Topic in Signal Processing (JSTSP).

Starting in 2024, JSTSP will include a series of articles on AI in Signal and Data Science. The series will serve as a platform for communicating state-of-the-art AI/ML research for signal and data, highlighting the research challenges that remain unanswered and further exploring innovative principles and solutions to resolving them.

Accordingly, we invite the submission of high-quality manuscripts in the relevant emerging sub-topics, papers which have not been published previously and are not currently under review by any publication venues. The initial scope of this series includes cutting-edge AI areas relevant to the broader signal and data science communities such as Explainable, Reliable, and Sustainable Machine Learning. 

The special series editorial team reserves the right to recommend submissions that are deemed out of scope or modest fit to be resubmitted to other regular SPS journals for consideration.

While manuscripts can be submitted at any time indicating for this special series, interested authors are strongly encouraged to make their submissions according to the following timetable to be considered for the inaugural 2024 issues of the first half of the year.  The timeline for additional articles in the series will be announced. 

Important Dates

• Manuscript Submission: July 1, 2023
• First Review Due: September 15, 2023
• Revised Manuscript Due: October 15, 2023
• Second Review Due: November 15, 2023
• Final Decision Due: December 15, 2023
• Publication Date: First Half of  2024

Editorial Team

• Xiao-Ping (Steven) Zhang (EIC-JSTSP), Toronto Metropolitan University & Tsinghua-Berkeley Shenzhen Institute
• Bhuvana Ramabhadran (Lead), Google
• Wenbo Ding, Tsinghua University
• Yonina C. Eldar, Weizmann Institute of Science
• Maria Sabrina Greco, University of Pisa
• Zhu Han, the University of Houston
• Yi Ma, UC Berkeley and Hong Kong University
• Helen Meng, Chinese University of Hong Kong
• Zheng-Hua Tan, Aalborg University
• Dacheng Tao, University of Sydney
• Zhou Wang, University of Waterloo
• Aylin Yener, Ohio State University

Additional details can be found on the Special Issue Deadlines page.