Yaqing Hou's Homepage

CEC-2025 Special Session on Memetic Computing

Organized by Yaqing Hou, Zexuan Zhu, Ferrante Neri, Chuan-Kang Ting, Maoguo Gong

Contact email: houyq@dlut.edu.cn

Website: https://www.hou-yq.com/

Supported by IEEE CIS Emergent Technologies Task Force on Memetic Computing (optional)

Scope and Topics

  The Special Session on Memetic Computing (MC) is organized by IEEE CIS Emergent Technologies Task Force on Memetic Computing. MC is a paradigm that employs memes, which are units of information, encoded in computational representations to solve problems. The concept of memes within MC is commonly understood as individual learning procedures, adaptive improvement procedures, or local search operators that enhance the effectiveness of population-based search algorithms. Additionally, new manifestations of memes, such as knowledge building-blocks, decision trees, artificial neural networks, fuzzy systems, and graphs, have been proposed to facilitate efficient problem-solving. These algorithms, frameworks, and paradigms inspired by memes have demonstrated considerable success in various real-world applications. The purpose of this special session is to provide researchers with a platform to share the latest advancements in theories, technologies, and practical applications of MC.
  The topics of this special session include but are not limited to the following topics:
  ● Single/Multi-objective/multi-tasking memetic algorithms
  ● Memetic algorithms for continuous or combinatorial optimization
  ● Theoretical studies that enhance our understandings on the behaviors of memetic computing
  ● Adaptive systems and meme coordination
  ● Novel manifestations of memes for problem-solving
  ● Cognitive, brain, individual learning, and social learning inspired memetic computation
  ● Novel competitive, collaborative and cooperative frameworks of memetic computation
  ● Memetic frameworks using surrogate or approximation methods to solve expensive and complex real-world problems
  ● Data mining, machine learning, knowledge learning and generative intelligence in memetic computation paradigm


Yaqing Hou
Dalian University of Technology, China
Email: houyq@dlut.edu.cn
Yaqing Hou received the Ph.D. degree in artificial intelligence from Interdisciplinary Graduate School, Nanyang Technological University, Singapore, in 2017. He is currently an Associate Professor with the College of Computer Science and Technology, Dalian University of Technology, Dalian, China. His research interests include computational and artificial intelligence, memetic computing, multiagent reinforcement learning, transfer learning and optimization. He is an Associate Editor of IEEE Transactions on Cognitive and Developmental Systems and is an Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence. He is also the Chair of the IEEE CIS Emergent Technologies Task Force on Memetic Computing. He has published more than 50 articles in international journals and conferences, including IEEE TEVC, IEEE TSMC, IEEE TETCI, IEEE TCSVT, IEEE TAI, AAMAS, ICRA, etc. He is now an Associate Editor for the Memetic Computing.

Zexuan Zhu
Shenzhen University, China
Email: zhuzx@szu.edu.cn
Zexuan ZHU is a Professor with the College of Computer Science and Software Engineering, Shenzhen University, China. He received his B.Sc degree from the Department of Computer Science and Engineering, Fudan University, China, in 2003 and the Ph.D degree from the School of Computer Science and Engineering, Nanyang Technological University, Singapore, in 2008. His research interests include computational intelligence, machine learning, and bioinformatics. He was an Associate Editor of IEEE Transactions on Evolutionary Computation (2017-2022) and is an Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence. He is also the Chair of the IEEE CIS Emergent Technologies Task Force on Memetic Computing.

Ferrante Neri
University of Surrey, UK
Email: f.neri@surrey.ac.uk
Ferrante Neri (Senior Member, IEEE) received the Laurea and Ph.D. degrees in electrical engineering from Politecnico di Bari, Bari, Italy, in 2002 and 2007, respectively, and the second Ph.D. degree in scientific computing and optimisation and the D.Sc. degree in computational intelligence from the University of Jyväskylä, Jyväskylä, Finland, in 2007 and 2010, respectively. Between 2009 and 2014, he was an Academy Research Fellow with the Academy of Finland to lead the project Algorithmic Design Issues in Memetic Computing. He was with De Montfort University, Leicester, U.K., between 2012 and 2019 and with the University of Nottingham, Nottingham, U.K., between 2019 and 2022. Since 2022, he has been with the University of Surrey, Guildford, as a Full Professor of machine learning and artificial intelligence and the Head of the Nature Inspired Computing and Engineering (NICE) Research Group. His research focuses on optimisation algorithms in the context of machine learning. He serves as an Associate Editor for Information Science and as the Deputy Managing Editor-in-Chief for the Memetic Computing Journal. Since 2019, his profile has been listed among the top 2% of scientists worldwide in the field of Artificial Intelligence and Image Processing, according to the Stanford World Ranking of Scientists.

Chuan-Kang Ting
National Tsing Hua University, Taiwan
Email: ckting@pme.nthu.edu.tw
Chuan-Kang Ting (Senior Member, IEEE) received the B.S. degree from National Chiao Tung University, Hsinchu, Taiwan, in 1994, the M.S. degree from National Tsing Hua University, Hsinchu, in 1996, and the Dr. rer. nat. degree in computer science from Paderborn University, Paderborn, Germany, in 2005. He is currently a Professor and the Chair of Department of Power Mechanical Engineering, National Tsing Hua University. His research interests include evolutionary computation, computational intelligence, machine learning, and their applications in machinery, manufacturing, ethics, music and arts. Dr. Ting is the Editor-in-Chief of IEEE Computational Intelligence Magazine and Memetic Computing, an Associate Editor of IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, and an Editorial Board Member of Soft Computing. He served as the IEEE Computational Intelligence Society (CIS) Newsletter Editor, the IEEE CIS Webmaster, the Chair of IEEE CIS Chapters Committee, and the Chair of IEEE CIS Creative Intelligence Task Force. He is an Executive Board Member of Taiwanese Association for Artificial Intelligence.

Maoguo Gong
Xidian University; Inner Mongolia Normal University, China
Email: gong@ieee.org
Maoguo Gong (Fellow, IEEE) received the B.Eng. and Ph.D. degrees from Xidian University, Xi’an, China, in 2003 and 2009, respectively. Since 2006, he has been a Teacher with Xidian University, where he was promoted to an Associate Professor and a Full Professor in 2008 and 2010, respectively, both with exceptive admission. He has authored more than 100 papers in journals and conferences. He holds more than 20 granted patents as the First Inventor. He is leading or has completed more than 20 projects as the Principal Investigator, funded by the National Natural Science Foundation of China, the National Key Research and Development Program of China, and others. His research interests include computational intelligence, with applications to optimization, learning, data mining, and image understanding.
Dr. Gong is an Executive Committee Member of Chinese Association for Artificial Intelligence and a Senior Member of Chinese Computer Federation. He was a recipient of the prestigious National Program for Support of the Leading Innovative Talents from the Central Organization Department of China, the Leading Innovative Talent in Science and Technology from the Ministry of Science and Technology of China, the Excellent Young Scientist Foundation from the National Natural Science Foundation of China, the New Century Excellent Talent from the Ministry of Education of China, and the National Natural Science Award of China. He is an Associate Editor or an Editorial Board Member for more than five journals, including IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION and IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS.

Potential Contributors

Yew-Soon Ong, Nanyang Technological University, Singapore
Tang Ke, Southern University of Science and Technology, China
Donald C. Wunsch, University of Missouri Rolla, USA
Ying-ping Chen, National Chiao Tung University, Taiwan
Meng-Hiot Lim, Nanyang Technological University, Singapore
Licheng Jiao, Xidian University, China
Natalio Krasnogor, Newcastle University, UK
Steven Gustafson, GE Global Research, USA
Kay Chen Tan, City University of Hong Kong, Hongkong
Yaochu Jin, University of Surrey, UK
Chuan-Kang Ting, National Chung Cheng University, Taiwan
Jim Smith, The University of the West of England, UK
Ruhul Sarker, The University of New South Wales, Australia
Shaheen Fatima, Loughborough University, UK
Chi Keong Goh, Advanced Technology Centre, Rolls-Royce Singapore Pte. Ltd, Singapore
Swagatam Das, Indian Statistical Institute, India
Gary Lee Kee Khoon, Institute of High Performance Computing, A-Star, Singapore
Yanqing Zhang, Georgia State University, USA
Pablo Moscato, The University of Newcastle, Australia
Carlos Cotta, Universidad de Málaga, Spain
Anna Kononova, Heriot-Watt University, UK
Ernesto Mininno, Technical University of Bari, Italy
Bo Liu, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China
Liang Feng, Chongqing University, China