Call for papers

Special Session on Evolutionary Quantum inspired Machine Learning Algorithms

IEEE Congress on Evolutionary Computation (IEEE CEC 2021)

28 June 2021 - 1 July 2021

Krakow, Poland





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 Researchers and scientist are invited to submit original and unpublished research that include theoretical and experimental results of advances scalable machine learning techniques in the following and other related areas.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 2021) (https://cec2021.mini.pw.edu.pl/en), at Krakow, Poland in between 28 June 2021 -1 July 2021. All papers should be prepared according to the CEC 2021 policy. 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, 2021

Paper Acceptance Notification Date: March 22, 2021

Final Paper Submission and Early Registration Deadline: April 7, 2021

Conference: 28 June-1 July, 2021



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. Manoranjan Mohanty

Senior Lecturer, Center for Forensic Science at the Faculty of Science,

University of Technology Sydney (UTS), Sydney, Australia

Email: manoranjan.mohanty@uts.edu.au

Dr. Omprakash Kaiwartya

Senior Lecturer, School of Science & Technology,

Nottingham Trent University (NTU), United Kingdom (UK)

Email: omprakash.kaiwartya@ntu.ac.uk


Biography:

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 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 University of Technology Sydney, IIT Indore, CSIR-CEERI Pilani, and C-DAC Pune.

Dr. Neha Bharill is currently working as an Assistant Professor in the Discipline of Computer Science & Engineering, Ecole Centrale School of Engineering at Mahindra University, Hyderabad. She completed Ph.D. in computer science and engineering from the Indian Institute of Technology Indore, India, in 2018. 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 the member of Soft Computing research Society. She has published over 11 referred journals and 15 conference papers of international repute. She is the reviewer of the IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Big Data, Swarm and Evolutionary Computation of Elsevier and the Complex & Intelligent Systems of Springer and many more. He is also working on some research projects in the collaboration with the IIT Indore, Indian Institute of Soybean Research Indore, and C-DAC Pune.

Dr. Manoranjan Mohanty is a lecturer in the Center for Forensic Science at the Faculty of Science, UTS. His research interest is on digital forensics and cybersecurity, with a current focus on multimedia forensics and AI for forensics. Manoranjan received his Ph.D. in Computer Science from the National University of Singapore, Singapore in 2014. After that, he spent a year as an ERCIM Alain Bensoussan research fellow at SICS Swedish ICT, Sweden, and two years as a research fellow at New York University. Before joining UTS, he was a Lecturer in Digital Security at the University of Auckland, New Zealand.

Dr. Omprakash Kaiwartya is currently working as a Senior Lecturer at the School of Science & Technology, Nottingham Trent University (NTU), UK. He is also the Course Leader for MSc. Engineering (Electronics, Cybernetics & Communications) in the department. Previously, He was a Research Associate at the Northumbria University, Newcastle, UK, in 2017 and a Postdoctoral Research Fellow at the Universiti Teknologi Malaysia (UTM) in 2016. He received his Ph.D. degree in Computer Science from Jawaharlal Nehru University, New Delhi, India, in 2015. He is the Fellow in Higher Education Academy (FHEA), UK. He is also Senior Member in IEEE, USA and Professional Member in British Computer Society (BCS), UK. His research interest focuses on future smart technologies for diverse domain areas focusing on Transport, Healthcare, and Industrial and Agriculture Production. His recent scientific contributions are in Drone Enabled Networking, E-Mobility Centric Electric Vehicles, IoT Enabled Smart Services, Connected Vehicles, and Next Generation Wireless Systems. He is serving as Associate Editor and/or Guest Editor of reputed SCI Journals including, IEEE Internet of Things Journal, IEEE Access, IET Intelligent Transport Systems, Springer, EURASIP Journal on Wireless Communication and Networking, MDPI Sensors and Electronics, Wiley-Hindawi Wireless Communications and Mobile Computing, Wiley Transactions on Emerging Technologies, Ad-Hoc & Sensor Wireless Networks, Transactions on Internet and Information Systems.