Call for Papers

IEEE IJCNN 2020: Special Session on Advance Scalable Machine Learning Techniques for NGS Analysis of Big Data

IEEE World Congress on Computational Intelligence WCCI 2020 , Glasgow, Scotland (UK), July 19 - 24, 2020

Scope and Aim:

With the technological advancements, the next generation sequencing (NGS) data is generated at an exponential rate coined as Big Data. The field of computational bioinformatics is facing challenges in the analysis, handling, and processing of this ever-increasing quantity of next-generation sequencing data. Data storage limitations are now eclipsed by problems that limit the curator’s ability to compile, analyze, and interpret data in a useful and timely manner. For the accurate analysis of huge NGS data, advanced technologies or methods are needed that solve the issues of computational time and extract valuable information, in a realistic and practical time frame, without compromising the quality of models. Therefore, there is an urgent need to innovate the advance scalable machine learning approaches. These approaches can address the important issues of data analysis, data pre-processing of computational bioinformatics that involve NGS data analysis through various scalable machine learning techniques such as clustering, classification, feature selection. Some advanced machine learning techniques such as deep neural networks, probabilistic graphical models, support vector machines, semi-supervised learning, convolutional neural networks, hidden Markov models, Bayesian learning, random forests, association rule learning, reinforcement learning and multiobjective optimization have already been proved to be very effective in learning from huge datasets in many research fields. Thus, it is of great interests to see how these advanced scalable machine learning techniques perform on computational bioinformatics problems.

Topics:

The main aim of this special session is to provide a forum to the scientists and researchers of this field to exchange the latest advances in theories and experiments in this field of research. Researchers are invited to submit original and unpublished works that deal with theoretical and experimental results of advanced scalable machine learning techniques in the following and other related areas.

  • Scalable machine learning methods to handle Big Data (including text data, audio, video, image etc.)
  • Sequence analysis including next-generation sequencing
  • Pattern recognition for genomics
  • Big Data analytics for bioinformatics applications
  • Scalable Next Generation Sequence analysis tools
  • Genome data analysis tools
  • Scalable multi-objective optimization approaches for Big Data.
  • Probabilistic Big Data approaches for NGS analysis.
  • Scalable feature selection approach for Genomics.
  • Advanced Soft Computing approaches (eg: Scalable Deep Learning approaches, Semi-Supervised Learning, Neural Networks) applied to Bioinformatics.

Important Dates:

  • Deadline of Full Paper Submission: January 15, 2020
  • Notification of Paper Acceptance: March 15, 2020
  • Camera Ready Submission of Accepted Papers: April 15, 2020
  • Registration Deadline for Authors follows the general registration dates of WCCI 2020.
  • IEEE WCCI 2020, Glasgow, Scotland, UK : July 19-24, 2020

Submission Guidelines:

This special session will be held in 2020 International Joint Conference on Neural Networks-IJCNN (wcci2020.org/ijcnn-sessions/), a part of 2020 IEEE World Congress on Computational Intelligence (https://wcci2020.org/ ) (Glasgow, Scotland, United Kingdom, July 19-24, 2020). All papers should be prepared according to the IJCNN 2020 policy and should be submitted electronically using the conference website (https://wcci2020.org/ ) . To submit your paper to this special session, you have to choose our special session on the submission page. All papers accepted and presented at IEEE IJCNN 2020 will be included in the conference proceedings published by IEEE Explore, which are typically indexed by EI. The papers published in the conference proceeding of IEEE IJCNN 2020 will be invited to prepare and submit the extended versions of their papers in highly reputed SCI Journals, possibly appearing in a special section of the journal (in the process of approval from Journal EiC).

Session Chairs:

  • Dr. Neha Bharill, Department of Computer Science and Engineering, Mahindra Ecole Centrale, Hyderabad, India, neha.bharill@mechyd.ac.in.
  • Prof. Aruna Tiwari, Department of Computer Science and Engineering, Indian Institute of Technology Indore, India, artiwari@iiti.ac.in.
  • Dr. Prashant K Gupta, Amity School of Engineering and Technology, Noida, India, guptaprashant1986@gmail.com.
  • Dr. Milind Ratnaparkhe, Department of Biotechnology, Indian Institute of Soybean Research Indore Under Indian Council of Agricultural Research, India, milind.ratnaparkhe@gmail.com.

Biography of the Session Chairs:

Dr. Neha Bharill is currently working as an Assistant Professor in the Department of Computer Science & Engineering at Mahindra Ecole Centrale, 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 the member of Soft Computing research Society. She has published more than 25 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 served as the program committee (PC) member of IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE Symposium Series on Computation Intelligence (SSCI), International Conference on Soft Computing for problem solving (SocPros), IEEE Congress on Evolutionary Computation (CEC). 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.

Prof. Aruna Tiwari is currently working as an Associate Professor in the Discipline of Computer Science & Engineering in Indian Institute of Technology Indore since 2012. Her research interests mainly are soft computing, machine learning, specifically with artificial neural networks, fuzzy clustering, evolutionary computation and their applications to bioinformatics, medical diagnosis. She also works in the area of scalable soft computing algorithm for big data and Hardware realization of Soft computing models. Currently she is working with CSIR-Central Electronics Engineering Research Institute, Pilani for the problems related to hardware realization of Soft computing models. She is member of various research societies like Computer Society of India, IEEE Computational Intelligence Society, Soft Computing research Society. She has published over 21 referred journals and 30 conference papers of international repute which are IIT Indore affiliated. Dr. Aruna Tiwari is currently the Principal Investigator of a major research project funded by Council of Scientific & Industrial Research (CSIR).

Dr. Prashant K Gupta is currently working as Assistant Professor in the Discipline of Computer Science & Engineering in Amity School of Engineering and Technology, Amity University, Noida, India. His research interests include fuzzy logic, computing with words, linguistic optimization, E-Health, and Machine learning. He is a member of IEEE and IEEE SMC. He has published articles in various journals such as IEEE Transactions on Fuzzy Systems, Fuzzy Sets and Systems, Applied Soft Computing, and Granular Computing. He has also published articles in core A ranked conferences such as Fuzz- IEEE and IEEE SMC. He is a reviewer in Journal of Applied Soft Computing.

Dr. Milind Ratnaparkhe is a senior scientist at Indian Institute of Soybean Research, Indore under Indian Council of Agricultural Research, India. He has over 20 years of research experience in the field of plant genomics, genetics and biotechnology His current research involves comparative and functional genomics studies to identify genes for important traits and in the development of new computational and bioinformatic tools for the analysis of plant genomes. He has published more than 20 Journal Papers of International Repute. He is currently the Principal Investigator of a major research project funded by ICAR-National Agriculture Science Funds, DRDO and many more.