NCSI: Cognitive Intelligence with EEG Deep Learning on Spark

Status	Completed
Mentor Name	Hong Lin
Mentor's XSEDE Affiliation	Campus Champion
Mentor Has Been in XSEDE Community	1-2 years
Project Title	Cognitive Intelligence with EEG Deep Learning on Spark
Summary	We will investigate the performance and the scalability of deep learning using electroencephalogram data (EEG) on the Spark platform. This study will extend the scope of current EEG data processing and modeling and evaluate its impacts to cognitive intelligence.
Job Description	In this project, the student will work on feature extraction from EEG data and perform thorough testing to maximize the recognition rates of the brain state deep learning models. The student will develop deep learning algorithms in the map-reduce framework on Spark, and implement and test the algorithms to ensure real-time processing of the EEG data. The challenge of modeling brain waves is to contemplate the rigorous time series analysis of brain waves to decipher trend, irregularities, cycles, seasonality and other variations among waves during different states. Therefore, feature extraction is an important part of EEG data analysis. The project aims to address the complexity of classification of brain waves data by modeling the major brain waves and achieve an efficient and predictable brain wave modeling system which has potential application in hospitality and clinical industry for self-controlled deep brain relaxation and early diagnosis of various brain abnormalities respectively. To ensure real-time processing of the EEG data and instant brain state classification, high performance deep learning model on the big data analysis platform Spark will be used to perform dynamic EEG data classification and testing. The deep learning model will be implemented in the map-reduce platform for big data analysis.
Computational Resources	We will use a high performance computing allocation from a XSEDE constitutional institution to implement the project. In recent years, we used NCSA's Blue Waters Allocation in education and research projects for student interns. We have a local cluster that can be used in daily development and testing activities.
Contribution to Community
Position Type	Apprentice
Training Plan	The student is a graduating senior at the University of Houston-Downtown. He has taken a course in statistical and machine learning and has the basic knowledge about EEG data analysis. He will study deep learning and Spark in the winter break. The faculty mentor used the Spark platform on Blue Waters Supercomputer in a summer big data analytics course, and can help the student to get started.
Student Prerequisites/Conditions/Qualifications	None
Duration	Semester
Start Date	01/14/2019
End Date	04/08/2019