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.

[Show all publications]

Latest publications:

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)

Food4You: A Personalized System for Adaptive Mealtime Situations for Elderly (Oct 2017)
Shahina Begum, Birgitta Kerstis , Shaibal Barua, Hanna Westerlund , Cecilia Hjortsberg
Medicinteknikdagarna 2017 (MTD 2017)

In-Vehicle Stress Monitoring Based on EEG Signal (Jul 2017)
Shahina Begum, Shaibal Barua, Mobyen Uddin Ahmed
International Journal of Engineering Research and Applications (IJERA)

Vehicle Driver Monitoring: sleepiness and cognitive load (May 2017)
Emma Nilsson , Christer Ahlström , Shaibal Barua, Carina Fors , Per Lindén , Bo Svanberg , Shahina Begum, Mobyen Uddin Ahmed, Anna Anund
Swedish National Road and Transport Research Institute (VTI) (VTI rapport 937A)

Classifying drivers’ cognitive load using EEG signals (May 2017)
Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum
14th International Conference on Wearable, micro & Nano Technologies (pHealth2017)