Mobyen Uddin Ahmed, Postdoctoral research fellow

Mobyen Uddin Ahmed is postdoctoral researcher in Intelligent Systems group and a member of ESS-H - Embedded Sensor Systems for Health Research Profile.

He is involved in research and development since 2005 after completing his M.Sc. in Computer Engineering (thesis) from Dalarna University, Sweden. He received his PhD (thesis) in computer science in 2011 from Mälardalen University. He has completed one postdoctoral study between the years 2012 and 2014 in Computer Science and Engineering (Center for Applied Autonomous Sensor Systems) at School of Science and Technology, Örebro University, Sweden

His research focuses on developing intelligent systems in medical applications. Mobyen is trying to invent personalized and adaptive methods, techniques to develop a computer based system in medical application. His research areas are case-based reasoning, datamining, fuzzy logic, diagnosis, treatment and knowledge/experience sharing.

Available theses

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Latest publications:

Big Data Analytics in Health Monitoring at Home (Oct 2017)
Mobyen Uddin Ahmed, Shahina Begum
Medicinteknikdagarna 2017 (MTD 2017)

Vision-Based Remote Heart Rate Variability Monitoring using Camera (Oct 2017)
Hamidur Rahman, Mobyen Uddin Ahmed, Shahina Begum
4th EAI International Conference on IoT Technologies for HealthCare (HealthyIOT'17)

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)

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)

Multi-parameter Sensing Platform in ESS-H and E-care@home (Jun 2017)
Mobyen Uddin Ahmed, Maria Lindén
Joint conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) (EMBEC & NBC’17)

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)

PhD students supervised as assistant supervisor:

Hadi Banaee (former)
Hamidur Rahman
Shaibal Barua

MSc theses supervised (or examined):
Thesis TitleStatus
Feature Selection through Artificial Intelligence for EEG Signal Classification available
A Decision Support System for medical diagnosis using Data Mining and Machine Learning available
Activity monitoring in daily life using Angel available
An intelligent system for driver cognitive load detection using eye tracking data available
Artifact handling or filtering noise from the biological sensor signals i.e. ECG available
Correlation analysis among EEG, EOG and EMG signals for identification of ocular and muscle activities available
Detect drug abuse by AI processed eye movement data from a smart phone film available
Eye Tracking and Head Movement Detection available
GameAlyzer - a wearables and AI based system to monitor gambling and gaming available
Human Emotion Detection using Deep Learning available
Non-Contact Intelligent System to monitor driver’s alcoholic state using Biological Signals available
Smart Mirror to monitor Health Status using Biological Signals available
Machine Learning applied on embedded system recordings selected
A decision support system for stress diagnosis using ECG signal. finished
A Generic System-level framework for Intelligent Sensor Data Management finished
Artificial Intelligence Search Algorithms In Travel Planning finished
Artificial Intelligence Search Algorithms In Travel Planning finished
Business intelligent systems for small and medium enterprises. finished
Case-based reasoning in postoperative pain treatment finished
Clinical Decision Support System for Post operative Pain relief finished
Decision Support System for Lung Diseases (DSS) finished
Develop an Automated System for EEG Artifacts Identification finished
Develop Experience Reusing System by Combining Vector Space Model and Nearest Neighbour. finished
Efficient Remote Instruction Procedures Using Case Base Reasoning finished
Experience Sharing Over the InternetCase study e-learning finished
Feature Extraction From Sensor Data To Represent And Matching Cases For Patient Health Care finished
Feature selection of EEG-signal data for cognitive load finished
Intelligent System for Monitoring Physiological Parameters Using Camera finished
Investigation of Feature Optimization Algorithms for EEG Signal Analysis For Monitoring the Drivers finished
Multi-Sensor Information Fusion for Monitoring Driver’s Level of Performance finished
Online fuzzy case-based individual stress diagnosing system finished
Textual CBR system using domain specific ontology finished
Using NLP and context for improved search result in specialized search engines finished