On July 11, 2021, the top decision-making body of IEEE Congress on Evolutionary Computation officially confirmed the new Editor in Chief of IEEE Transactions on Neural Networks and Learning Systems, an internationally authoritative journal (TNNLS). Chongqing University’s Professor Song Yongduan, dean of the School of Automation, is elected as the new Editor in Chief of TNNLS. Song will officially take office on January 1, 2022. Song is the first professor from a Chinese college or university that has served as the editor in chief of TNNLS.

TNNLS chooses its editor in chief from researchers all over the world once every 6 years, following strict procedures. Seven top researchers in this area are appointed to score the candidates anonymously in terms of their academic influence, working experience with international journals, future development planning and implementation measures for TNNLS, and contributions they have made in IEEE services. Two finalists with the highest scores will be selected from the candidates. After that, the two finalists will participate in a video defense, followed by secret balloting. The one with more votes will be elected as the Editor in Chief. Finally, Song Yongduan was elected as the new Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems.

TNNLS was formerly IEEE Transactions on Neural Networks, and was founded by IEEE in 1990. It currently has more than 150 editorial board members worldwide. In 2021, the latest influence factor of TNNLS was 10.451, ranking at the 3rd place of 53 journals in the COMPUTER SCIENCE category of JCR journals. At present, it is in Zone I of the Journal Division of the Chinese Academy of Sciences. The journal falls within the interdisciplinary area of artificial intelligence, machine learning and computer science. It mainly publishes the latest research results related to neural networks and learning systems. It is the flagship journal of IEEE Congress on Evolutionary Computation and the international top journal in neural networks and learning systems.