CFP
ICMDE2020: International Conference on Computational Methods and Data Engineering SRM University Delhi-NCR, Sonepat (Haryana), India Sonepat, India, January 30-31, 2020 |
Conference website | https://www.srmuniversity.ac.in/icmde2020/ |
Submission link | https://easychair.org/conferences/?conf=icmde2020 |
Abstract registration deadline | December 8, 2019 |
Submission deadline | December 8, 2019 |
ICMDE 2020
The primary goal of the conference is to provide opportunities for academicians and scientists from academic institutions, industries, policy makers and professionals from various fields in a global realm to present their research contributions and opinions on one forum and interact with members inside and outside their own particular disciplines. Prospective Researchers/ Authors are invited to submit their original and unpublished research work describing their theoretical/ experimental work in the following tracks:
TRACK A : COMPUTATIONAL METHODS FOUNDATIONS
Learning theory, Optimization Methods, Statistical learning, Evolutionary Computation, Generalization in neural, fuzzy and evolutionary learning, Learning Classifiers, Probabilistic and statistical models and theories, Parallel and distributed learning, Scientific data and Big Data Engineering, Scalable analysis and learning, Data sampling and reduction, High dimensional data, feature selection and feature transformation, High performance computing for data analytics, Hybridization intelligent techniques
TRACK B : COMPUTATIONAL METHODS AND KNOWLEDGE DISCOVERY
Computational Methods for Knowledge discovery models and systems, Computational Methods in Human-machine interaction for knowledge discovery and management, Computational Methods in Nature inspired and evolutionary computation for knowledge discovery, Computational Methods for Knowledge based neural networks, Computational Methods for Knowledge discovery from heterogeneous, unstructured and multimedia data, Computational Methods for Knowledge discovery in social networks, Computational Methods for Data and knowledge visualization, Computational Methods in High performance computing for Knowledge discovery
TRACK C : COMPUTATIONAL METHODS AND DATA ENGINEERING
Learning theory, Optimization Methods, Statistical learning, Evolutionary Computation, Generalization in neural, fuzzy and evolutionary learning, Learning Classifiers, Probabilistic and statistical models and theories, Parallel and distributed learning, Scientific data and Big Data Engineering, Scalable analysis and learning, Data sampling and reduction, High dimensional data, feature selection and feature transformation, High performance computing for data analytics, Hybridization intelligent techniques
TRACK B : COMPUTATIONAL METHODS AND KNOWLEDGE DISCOVERY
Computational Methods for Knowledge discovery models and systems, Computational Methods in Human-machine interaction for knowledge discovery and management, Computational Methods in Nature inspired and evolutionary computation for knowledge discovery, Computational Methods for Knowledge based neural networks, Computational Methods for Knowledge discovery from heterogeneous, unstructured and multimedia data, Computational Methods for Knowledge discovery in social networks, Computational Methods for Data and knowledge visualization, Computational Methods in High performance computing for Knowledge discovery
TRACK C : COMPUTATIONAL METHODS AND DATA ENGINEERING
Computational Methods in Big data Engineering, Computational Methods in High-Performance Computing, Computational Methods in Machine learning over the Cloud, Computational Methods in bioinformatics, computational biology, health and medical analytics, Computational Methods in Intelligent system modeling, designing and computing, Computational Methods in Cognitive Science and Artificial Intelligence, Computational Methods in machine learning and deep learning, Computational Methods in pattern recognition, Computational Methods in Image Processing, Computational Methods in Intelligent Information Retrieval, Computational Methods in Scientific analytics and real time decision making for Data Engineering, Big data Engineering foundations, analytics and visualization
TRACK D : APPLICATIONS
Bioinformatics, Computational neuroscience, Pattern Recognition, Image processing, Computer vision, Business, Social science, Human activity recognition
Bioinformatics, Computational neuroscience, Pattern Recognition, Image processing, Computer vision, Business, Social science, Human activity recognition
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
- Full papers
- Posters
Committees
Program Committee
- Prof. V. Samuel Raj
- Prof. Manish Bhalla
Organizing committee
- Dr. Sanjay Kumar
- Dr. Arvind Kumar
Contact
All questions about submissions should be emailed to icmde2020@gmail.com