Special Session on Hybrid Metaheuristics for Automatic Data Clustering and Analysis

Organizer: Prof. (Dr.) Siddhartha Bhattacharyya

Senior Research Scientist in VSB Technical University of Ostrava, Ostrava, Czechia.
Principal and Full Professor of Computer Application, RCC Institute of Information Technology, Kolkata, India

Aim and Scope
Of late, scientists have stressed upon the hybrid metaheuristics in particular, given the fact that the hybrid metaheuristics, being a judicious combination of several other metaheuristics, algorithms from mathematical programming, constraint programming, or machine learning algorithms, have been found to be more robust and failsafe. This is primarily due to the fact that the vision of hybridization is to combine different metaheuristics such that each of the combination supplements the other in order to achieve the desired performance. Typical examples use fuzzy-evolutionary, neuro-evolutionary, neuro-fuzzy evolutionary, rough-evolutionary approaches to name a few. Recently, chaos theory has also found wide applications in evolving efficient hybrid metaheuristics. The advent of the quantum computing paradigm has also given an impetus to evolving time efficient hybrid metaheuristics, where the principles of quantum mechanics are conjoined successfully to enhance the real time performance of the hybrid metaheuristics.
Clustering or cluster analysis can be considered as a process of partitioning a dataset of different objects into a meaningful group of similar objects. Several methods can be used for successful clustering namely, Partitioning methods, Hierarchical clustering, Fuzzy clustering, Density-based clustering, Model-based clustering etc. Among these methods, the K-means [3] performs very well. However, it requires an a priori knowledge about the number of clusters present in the dataset. Automatic clustering, on the other hand, is intended to find out the optimal number of clusters from a dataset without having the prior knowledge about the number of clusters, which may be useful during the segmentation and classification purpose. Basically this requirement has dragged the researchers into the field of automatic clustering techniques.
The main objective of this Special Session is to bring together recent advances and trends in methodological approaches, theoretical studies, mathematical and applied techniques related to the use of hybrid metaheuristics for automatic clustering of data and its analysis. We invite researchers to contribute original work related to the theoretical advancements in this field with applications to different facets of data analysis and understanding. We are soliciting contributions on (but not limited to) the following:

  1. Hybrid metaheuristics
  2. Memetic algorithms
  3. Parallel metaheuristics
  4. Tabu search and simulated annealing
  5. Novel nature inspired metaheuristics
  6. Variable neighborhood search and memory-based optimization
  7. Quantum inspired hybrid metaheuristics
  8. Multi-valued quantum logic based quantum metaheuristics
  9. Quantum entanglement enhanced metaheuristics
  10. Single objective solutions for linearly separable clusters
  11. Multi-objective incarnations for non-linearly separable clusters
  12. Cluster analysis indices
  13. Image processing and pattern recognition
  14. Medical Image Analysis
  15. Remote Sensing Applications
  16. Big Data Analysis
  17. Portfolio Optimization
  18. Bioinformatics


Prof. (Dr.) Siddhartha Bhattacharyya

Siddhartha Bhattacharyya did his BS in Physics, B. Tech. and M. Tech. from University of Calcutta, India in 1995, 1998 and 2000 respectively. He completed PhD in Computer Science and Engineering from Jadavpur University, India in 2008. He is the recipient of the University Gold Medal from the University of Calcutta for his Masters. He is the recipient of the coveted National Award Adarsh Vidya Saraswati Rashtriya Puraskar for excellence in education and research in 2016. He is the recipient of the Distinguished HoD Award and Distinguished Professor Award conferred by Computer Society of India, Mumbai Chapter, India in 2017. He is the recipient of the coveted Bhartiya Shiksha Ratan Award conferred by Economic Growth Foundation, New Delhi in 2017. He received the NACF-SCRA, India award for Best Faculty for Research in 2017. He received the Honorary Doctorate Award (D. Litt.) from The University of South America and the South East Asian Regional Computing Confederation (SEARCC) International Digital Award ICT Educator of the Year in 2017. He received the Rashtriya Shiksha Gaurav Puraskar from Center for Education Growth and Research, India in 2017. He received the Young Scientist (Science & Technology) Award from CSERD, India in 2018.
He is currently a Senior Research Scientist in VSB Technical University of Ostrava, Ostrava, Czechia. He is also the Principal of RCC Institute of Information Technology, Kolkata, India. In addition, he is also serving as a Full Professor of Computer Application of the institute. Prior to this, he was a Full Professor of Information Technology of RCC Institute of Information Technology, Kolkata, India. He served as the Head of the Department from March, 2014 to December, 2016. Prior to this, he was an Associate Professor of Information Technology of RCC Institute of Information Technology, Kolkata, India from 2011-2014. Before that, he served as an Assistant Professor in Computer Science and Information Technology of University Institute of Technology, The University of Burdwan, India from 2005-2011. He was a Lecturer in Information Technology of Kalyani Government Engineering College, India during 2001-2005.
He is a co-author of 4 books and the co-editor of 16 books and has more than 200 research publications in international journals and conference proceedings in avenues such as Elsevier, Springer and ACM. He has got two PCTs to his name. He has been the General Chair as well as the member of the organizing and technical program committees of several international conferences. He has been the Lead Guest Editors of several Special Issues with different international journals. He is the Editor of International Journal of Pattern Recognition Research since January 2016 and the founding Editor in Chief of International Journal of Hybrid Intelligence; Publisher: Inderscience. He is the member of the editorial board of Applied Soft Computing, Elsevier, B. V. He is the Associate Editor of International Journal of BioInfo Soft Computing, IEEE Access and Evolutionary Intelligence, Springer. He is serving as the Series Editors of IGI Global Book Series Advances in Information Quality and Management (AIQM), De Gruyter Book Series Frontiers in Computational Intelligence (FCI) , CRC Press Book Series Computational Intelligence and Applications, Wiley Book Series Intelligent Signal and Data Processing and Elsevier Book Series Hybrid Computational Intelligence for Pattern Analysis and Understanding. His research interests include soft computing, pattern recognition, multimedia data processing, hybrid intelligence and quantum computing. Siddhartha is a life fellow of OSI, fellow of IETE and IEI, India. He is also a senior member of IEEE, IETI, and ACM. He is a life member of ISRD, CSI, ISTE, IUPRAI and CEGR. He is a member of IET, IRSS, IAENG, CSTA, IAASSE, IDES, ISSIP and SDIWC.


Prof. (Dr.) Siddhartha Bhattacharyya
RCC Institute of Information Technology
Canal South Road, Beliaghata, Kolkata, 700 015, India
Email: dr.siddhartha.bhattacharyya@ieee.org