SBDM2017 Symposium  @ SmartTechCon2017

Welcome to SBDM 2017 !

Scope of the Symposium

The International Symposium on Brain Data Mining (SBDM 2017) is pleased to invite you to respond to our Call for Submissions for SmartTechCon2017, to be held from 17 - 19 August 2017 at the REVA University, Bangalore, India.

The Symposium on Brain Data Mining provides an opportunity to establish the relationship between Application of Data Mining on Brain Dataset like EEG, ECoG, fMRI, and network with other faculties and students in the Conference. Presenter can contribute their research work, and seek quality feedback on their research areas. Symposium on Brain Data Mining (SBDM) provides an excellent discussion forum that provides the platform to researchers and practitioners from neurology, neurosurgery, computer science, data science, artificial intelligence, and neuroimaging technologies with the purpose of exploring the fundamental roles, interactions as well as practical impacts of Brain Informatics.

SBDM 2017 address the application of Data Mining, Machine learning, on emerging trends of Big Brain data analysis and management technology for brain research. Real-world applications of brain science including brain diseases like epilepsy, dementia, etc.

Technical Committee

Chair: Dr. Nasir Hussain, Queensland University of Technology, Australia
Prof. Dr. Pradeep Kr. Gupta, University of Pretoria, South Africa
Prof. Dr. Abdullah Aljumah, PSAU, Ministry of Education, Saudi Arabia
Dr. Mohammad Altaf, PSAU, Ministry of Education, Saudi Arabia
Prof. Ravindra Bhatta, Jaypee University of Information & Technology (JUIT), Waknaghat, India
Mr. Faisal Khan, University of Ferrara, Italy
Dr. Mayank Singh, KEC, Ghaziabad, India
Mr. JP Dixit, Ambalika Institute of Management and Technology, Lucknow, India
Dr. Muhammad Mazhar, Glocal University, India

Submission Guidelines

Submit your paper in IEEE format. Submitted work should be original and application oriented. Acceptance will be based on reviewer's comments that will address the strong and weak aspects with suggestions to improve the work.

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