2023 International Conference on Communication Networks and Machine Learning(CNML 2023)

Prof. Ying Tan


Prof. Ying Tan

Associate Editor of IEEE Transactions, Peking University, China

Associate editor of IEEE Transactions on Systems, Man and Cybernetics: Part B Cybernetics (2011-2013)

Editor-in-Chief of International Journal of Computational Intelligence and Pattern Recognition (IJCIPR)


Ying Tan is a full professor and PhD advisor at Peking University. He is the inventor of Fireworks Algorithm (FWA). He received his BEng, MS from Xidian University, and PhD from Southeast University, in 1985, 1988, and 1997, respectively. He worked as a professor of Faculty of Design, Kyushu University, Japan, in 2018, at Columbia University as senior research fellow in 2017, and at Chinese University of Hong Kong in 1999 and 2004-2005 as research fellow, etc. He serves as the Editor-in-Chief of IASEI Transactions on Swarm Intelligence, Research Reports on Computer Science (RRCS) and International Journal of Computational Intelligence and Pattern Recognition (IJCIPR), the Associate Editor of IEEE Transactions on Cybernetics (CYB), IEEE Transactions on Neural Networks and Learning System (NNLS), IEEE Systems, Man and Cybernetics Magazine, Neural Networks, Machine Learning with Applications, etc. He also served as an Editor of Springer’s Lecture Notes on Computer Science (LNCS) for 50+ volumes, and Guest Editors of several referred Journals, including IEEE/ACM Transactions on Computational Biology and Bioinformatics, Information Science, Neurocomputing, Natural Computing, Swarm and Evolutionary Optimization, etc. He is the founder general chair of the ICSI International Conference series since 2010 and the DMBD conference series since 2016. He is the president of International Association of Swarm and Evolutionary Intelligence (IASEI). He won the 2nd-Class Natural Science Award of China in 2009 and 2nd-Class Natural Science Award of Ministry of Education of China in 2019 and many best paper awards. His research interests include computational intelligence, swarm intelligence, deep neural networks, machine learning and data mining for information security and financial prediction, etc. He has published more than 380+ papers in refereed journals and conferences in these areas, and authored/co-authored 15 books, including “Fireworks Algorithm” by Springer in 2015, and “GPU based Parallel Implementation of Swarm Intelligence Algorithms” by Morgan Kaufmann (Elsevier) in 2016, and received 5 invention patents.

Speech title: Advance in Swarm Intelligence, Fireworks Algorithm and Applications

Abstract: Inspired from the collective behaviors of many swarm-based creatures in nature or social phenomena, swarm intelligence (SI) has been received attention and studied extensively, gradually becomes a class of efficiently intelligent optimization methods. Inspired by fireworks'explosion in air, the so-called fireworks algorithm (FWA) was proposed in 2010. Since then, many improvements and beyond were proposed to increase the efficiency of FWA dramatically, furthermore, a variety of successful applications were reported to enrich the studies of FWA considerably. In this talk, the novel swarm intelligence algorithm, i.e., fireworks algorithm, is briefly introduced and reviewed, then several effective improved algorithms are highlighted, individually. In addition, the multi-objective fireworks algorithm and the graphic processing unit (GPU) based FWA are also briefly presented, particularly the GPU-based FWA is able to speed up the optimization process extremely. Extensive experiments on benchmark functions demonstrate that the improved algorithms significantly increase the accuracy of found solutions, yet decrease the running time sharply. Finally, several typical applications of FWA, in particular, for big-data application, are presented in detail.