Shaibal Barua, Doctoral student


Shaibal Barua is a PhD student at Mälardalen University. In 2013 he received his MSc in Computer Science from Mälardalen University.

Shaibal's research area is in applied intelligent systems with the focus on multisensor information fusion, applied artificial intelligence, and machine learning. He is currently involved in the research project, Vehicle Driver Monitoring (VDM), that aim is to develop applications for safety systems to monitor drivers’ mental state and provides counter measurements to prevent/reduce accidents.

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Latest publications:

Automatic Driver Sleepiness Detection using EEG, EOG and Contextual Information (Jan 2019)
Shaibal Barua, Mobyen Uddin Ahmed, Christer Ahlström , Shahina Begum
Expert Systems with Applications (ESWA)

Real-time Biomass Characterization in Energy Conversion Processes using Near Infrared Spectroscopy - A Machine Learning Approach (Aug 2018)
Mobyen Uddin Ahmed, Peter Andersson , Tim Andersson , Elena Tomas Aparicio , Hampus Baaz , Shaibal Barua, Albert Bergström , Daniel Bengtsson , Jan Skvaril , Jesús Zambrano
10th International Conference on Applied Energy (ICAE2018)

Towards Distributed k-NN similarity for Scalable Case Retrieval (Jul 2018)
Shaibal Barua, Shahina Begum, Mobyen Uddin Ahmed
The Third Workshop on Synergies between CBR and Machine Learning ( CBRML 2018)

Automated EEG Artifact Handling with Application in Driver Monitoring (Nov 2017)
Shaibal Barua, Mobyen Uddin Ahmed, Christer Ahlström , Shahina Begum, Peter Funk
IEEE Journal of Biomedical and Health Informatics (J-BHI)

Distributed Multivariate Physiological Signal Analytics for Drivers’ Mental State Monitoring (Oct 2017)
Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum
4th EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'17)

Scalable Framework for Distributed Case-based Reasoning for Big data analytics (Oct 2017)
Shaibal Barua, Shahina Begum, Mobyen Uddin Ahmed
4th EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'17)