OverviewNowadays, big data has been attracting increasing attention from academia, industry and government. Big data is defined as the dataset whose size is beyond the processing ability of typical databases or computers. Big data analytics is to automatically extract knowledge from large amounts of data. It can be seen as mining or processing of massive data, and “useful” information can be retrieved from large dataset. Big data analytics can be characterized by several properties, such as large volume, variety of different sources, and fast increasing speed (velocity). It is of great interest to investigate the role of evolutionary computing (EC) techniques, including evolutionary algorithms and swarm intelligence algorithms for the optimization and learning involving big data, in particular, the ability of EC techniques to solve large scale, dynamic, and sometimes multi-objective big data analytics problems.
Topics of InterestThis special session aims at presenting the latest developments of EC techniques for big data problems, as well as exchanging new ideas and discussing the future directions of EC for big data. Original contributions that provide novel theories, frameworks, and solutions to challenging problems of big data analytics are very welcome for this Special Session. Potential topics include, but are not limited to:
- High-dimensional and many-objective evolutionary optimization
- Big data driven optimization of complex engineering systems
- Integrative analytics of diverse, structured and unstructured data
- Extracting new understanding from real-time, distributed, diverse and large-scale data resources
- Big data visualization and visual data analytics
- Scalable, incremental learning and understanding of big data
- Scalable learning techniques for big data
- Big data driven optimization of complex systems
- Human-computer interaction and collaboration in big data
- Big data and cloud computing
- Cross-connections of big data analysis and hardware
- Big data techniques for business intelligence, finance, healthcare, bioinformatics, intelligent transportation, smart city, smart sensor networks, cyber security and other critical application areas
- MapReduce implementations combined with evolutionary computation or swarm intelligence approaches
SubmissionPlease follow the IEEE CEC2016 instruction for authors and submit your paper via the IEEE CEC 2016 online submission system. Please specify that your paper is for the Special Session on Evolutionary Computation and Big Data.
Important DatesPaper Submission Deadline: 15 Jan 2016
Notification of Acceptance: 15 Mar 2016
Final Paper Submission Deadline: 15 Apr 2016
- Shi Cheng, University of Nottingham Ningbo, China, email@example.com
- Yuhui Shi, Xi'an Jiaotong-Liverpool University, Suzhou China, firstname.lastname@example.org
- Yaochu Jin, University of Surrey, Guildford, United Kingdom, email@example.com
- Bin Li, University of Science and Technology of China, Hefei, China, firstname.lastname@example.org
- Simone Ludwig, North Dakota State University, USA, email@example.com
- Yinan Guo, China University of Mining and Technology, Xuzhou, China, firstname.lastname@example.org
- Junfeng Chen, Hohai University, Changzhou, China, email@example.com
Biography of the ProposersShi Cheng received the Bachelor's degree in Mechanical and Electrical Engineering from Xiamen University, Xiamen, the Master's degree in Software Engineering from Beihang University (BUAA), Beijing, China, the Ph.D. degree in Electrical Engineering and Electronics from Liverpool University, Liverpool, United Kingdom, the Ph.D. degree in Electrical and Electronic Engineering from Xi’an Jiaotong-Liverpool University, Suzhou, China in 2005, 2008, and 2013, respectively. He is currently a research fellow with Division of Computer Science, University of Nottingham Ningbo, China. He has published more than 30 research articles in peer-reviewed journals and international conferences. His current research interests include swarm intelligence, multiobjective optimization, and data mining techniques and their applications.
Yuhui Shi received the PhD degree in electronic engineering from Southeast University, Nanjing, China, in 1992. He is a Professor in the Department of Electrical and Electronic Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, China. Before joining Xi'an Jiaotong-Liverpool University, he was with Electronic Data Systems Corporation, Indianapolis, IN. His main research interests include the areas of computational intelligence techniques (including swarm intelligence) and their applications. Dr. Shi is the Editor-in-Chief of the International Journal of Swarm Intelligence Research.
Yaochu Jin is currently a Professor of Computational Intelligence with the Department of Computing, University of Surrey, Guildford, U.K., where he heads the Nature Inspired Computing and Engineering Group. He is also a Finland Distinguished Professor awarded by Academy of Finland. His main research interests include computational intelligence, computational neuroscience and computational systems biology, with applications to complex engineering optimization, bioengineering, swarm robotics, and autonomous systems. His current research is funded by EU FP7, UK EPSRC and industries, including Intellas UK, Santander, Aero Optimal, Bosch UK and Honda. He has delivered 20 invited keynote speeches at international conferences. Dr Jin is the founding chair of the IEEE Symposium on Computational Intelligence in Big Data and Guest Editor of the IEEE Computational Intelligence Magazine special issue on Big Data. He is an Associate Editor of several international journals including IEEE TRANSACTIONS ON CYBERNETICS, IEEE TRANSACTIONS ON NANOBIOSCIENCE, and IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE and BioSystems. He is currently Vice President for Technical Activities, and IEEE Distinguished Lecturer. He was the recipient of the Best Paper Award of the 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. He is a Fellow of BCS and Senior Member of IEEE.
Bin Li received the B.S. degree from HeFei University of Technology, Hefei, China, in 1992, the M.Sc degree from Institute of Plasma Physics, China Academy of Science, Hefei, China, in 1995, and the Ph.D degree from University of Science and Technology of China, China in 2001. He is currently a professor with the School of Information Science and Technology, University of Science and Technology of China, Hefei, China. He has published more than 50 refereed publications. His major research interests include evolutionary computation, pattern recognition, and real-world applications. Dr. Li is the Founding Chair of IEEE CIS Hefei Chapter, and the founding Counselor of IEEE USTC Student Branch.
Simone Ludwig received the PhD degree from Brunel University, UK, in 2004. She is currently an associate professor at North Dakota State University, USA, conducting research in the area of computational intelligence. In particular, developing novel algorithms to address different optimization problems in the area of data mining (large data) and distributed computing. She has published around 90 peer-reviewed articles both in journals and conference proceedings. Dr. Ludwig has served as a co-chair, track chair, and tutorial chair for different conferences, as well as served on numerous conference program committees. In addition, she currently serves on the editorial board of 3 journals.
Yinan Guo received the PhD degree in control theories and their applications from China University of Mining and Technology, China, in 2003. From September 2000, she worked as a Lecturer, Associate professor and Professor in China University of Mining and Technology respectively. In 2012, she done cooperative research on computational intelligence as an Academic visitor in CERCIA, School of Computer Science, Birmingham University, UK. Her current research interests include interactive evolutionary algorithms, knowledge-inducing cultural algorithm, evolutionary multi-objective optimization, evolutionary dynamic optimizations and relevant real-world applications. Dr Guo has over 70 publications and six research projects in the above domains.
Junfeng Chen received the PhD degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2011. Currently, she is an associate professor in the College of IOT Engineering, Hohai University, Changzhou, China. Her research interests include swarm intelligence, artificial intelligence with uncertainty and big data analytics. She has published over 20 papers in international journals and conference