Call for papers

Special Session on Evolutionary Quantum inspired Machine Learning Algorithms

IEEE Congress on Evolutionary Computation (IEEE CEC 2022) Under the Umbrella of WCCI 2022 (Ranked A Conference)

18 July 2022 - 23 July 2022

Padua, Italy

Aims:

Quantum computing is the area of study focused on developing computer technology based on the principles of quantum theory, which explains the nature and behaviour of energy and matter on the quantum (atomic and subatomic) level. The development of a quantum computer, if practical, would mark a leap forward in computing capability far greater than that from the abacus to a modern-day supercomputer. Along with research on an actual quantum computer, quantum computing concepts have been utilized to make evolutionary quantum-inspired machine learning algorithms that work in classical computers. Evolutionary Computing (EC) has been on several occasions directly linked to quantum computing such as quantum evolutionary computation or evolutionary design for quantum computer design, etc. Evolutionary methods are a prime tool for the exploration and exploitation of quantum properties. These algorithms help to improve the performance of existing computing models and algorithms to perform better by using quantum computing concepts.



Scope and Topics:

The aim of this special session on evolutionary quantum machine learning algorithms is to provide a platform for researchers and scientist discuss latest advances in this field. Researchers and scientist are invited to submit original and unpublished research that include theoretical and experimental results of advances scalable machine learning techniques in the following and other related areas. The scope of this special session covers among others but not limited to the following topics:

  • Evolutionary quantum algorithms.

  • Evolutionary quantum inspired machine learning algorithms.

  • Classical evolutionary algorithms for design of quantum computers.

  • Evolutionary quantum inspired deep neural network learning algorithms.

  • Evolutionary quantum inspired hybrid neural network learning algorithms.

  • Evolutionary quantum inspired combinatorial optimization algorithms


Submission Guidelines:

This special session will be held in the IEEE Congress on Evolutionary Computation (IEEE CEC 2022) under the Umbrella of WCCI 2022 (Ranked-A conference) (https://wcci2022.org/), at Padua, Italy in between 18 July 2022 -23 July 2022. All papers should be prepared according to the WCCI 2022policy. Please check the conference webpage. To submit your paper to this special session, you have to choose our special session on the submission page.




Important Dates:

Paper submission Deadline: January 31, 2022

Paper Acceptance Notification Date: April 26, 2022

Final Paper Submission and Early Registration Deadline: May 23, 2022

Conference: 18 July-23 July, 2022



Special Session Organizers:


Dr. Om Prakash Patel

Assistant Professor, Department of Computer Science and Engineering,

École Centrale School of Engineering (MEC), Mahindra University

Hyderabad-500043, Telangana, India

Email: omprakash.patel@mahindrauniversity.edu.in

Dr. Neha Bharill

Assistant Professor, Department of Computer Science and Engineering,

École Centrale School of Engineering (MEC), Mahindra University

Hyderabad-500043, Telangana, India

Email:

neha.bharill@mahindrauniversity.edu.in

Dr. Mukesh Prasad

School of Computer Science,

Faculty of Information Technology,

University of Technology Sydney, Australia

Email: Mukesh.prasad@uts.edu.au


Dr. Khaldoon Dhou

Assistant Professor of Computer Information Systems

College of Business Administration

Texas A&M University - Central Texas

Associate Editor, International Journal of Entertainment Technology and Management

Email: khaldoondhou@gmail.com



Biography:

Dr. Om Prakash Patel Dr. Om Prakash Patel is currently working as an Assistant Professor in the Department of Computer Science & Engineering, Ecole Centrale School of Engineering at Mahindra University, Hyderabad. He has done Ph.D. in computer science and engineering from the Indian Institute of Technology Indore, India, in 2018. His current research interests include quantum computing-inspired neural network learning algorithms, pattern recognition, hybrid neural network, and deep learning. He is a member of IEEE, IEEE CIS, and Soft Computing Research Society. He has published various journal papers including IEEE Transactions, SCI Indexed Journals of International ranked conferences. He has also received two best paper awards. He is the reviewer of the neural processing letters, soft computing Springer, IEEE SSCI, Inderscience journals, and many more. He is also working on some research projects in the collaboration with the IIT Indore, IISR Indore, CSIR-CEERI Pilani, and C-DAC Pune.


Dr. Neha Bharill is currently working as an Assistant Professor in the Department of Computer Science Engineering at Mahindra University, Ecole Centrale School of Engineering, Hyderabad, India. Her current research interests include fuzzy sets and systems, Big Data, pattern recognition, data mining, machine learning, scalable machine learning approaches for Genome Identification and Next Generation Sequence Analysis. She is a member of IEEE, IEEE CIS, and Soft Computing Research Society. She has published more than 30 peer-reviewed papers in top-tier journals and conferences including IEEE Transactions on Emerging Topics in Computing, IEEE Transactions on Big Data, IEEE, Access, Neurocomputing Elsevier, Soft Computing Springer, Fuzz-IEEE, WCCI, ICONIP, SSCI and many more. She has served as chair for a number of conferences, including WCCI 2015, SCCI 2019, SocPros 2019, SMC 2019. She is the reviewer of several IEEE journals and conferences including IEEE Transactions on Big Data, IEEE Transactions on Fuzzy Systems, IEEE Transactions on cybernetics, IEEE Transactions on Cyber-Physical systems, IEEE Transactions on Emerging Topics in Computational Intelligence, and many more.


Dr. Mukesh Prasad is a Senior Lecturer at the School of Computer Science in the Faculty of Engineering and IT at UTS who has made substantial contributions to the fields of machine learning, artificial intelligence, and the internet of things. His research interests include also big data, computer vision, brain-computer interface, and evolutionary computation. He is working also in the evolving and increasingly important fields of image processing, data analytics, and edge computing, which promise to pave the way for the evolution of new applications and services in the areas of healthcare, biomedical, agriculture, smart cities, education, marketing, and finance. His research has appeared in numerous prestigious journals, including IEEE/ACM Transactions, and at conferences, and he has written more than 100 research papers.


Dr. Khaldoon Dhou completed his Ph.D. in Computing and Information Systems from the University of North Carolina at Charlotte. He also did his post-doctoral fellowship in Data Science and Business Analytics at NC Complex Systems Institute. He worked as a visiting assistant professor of computer science at the University of Missouri St. Louis, and he was also a visiting assistant professor of MIS at Drury University. He is currently an assistant professor of CIS at Texas A&M University-Central Texas. Dr. Dhou served as a program committee member for many international conferences, and he is an associate editor for the International Journal of Entertainment Technology and Management. He also published many articles in highly reputable venues such as International Conference on Computational Science, Applied Soft Computing, IEEE Internet of Things Journal, and Future Generation Computer Systems.