Mobyen Uddin Ahmed, Senior Lecturer

E-mail:
mobyen.ahmed@mdh.se
Room:
U1-123
Phone:
+46-021-107369
Phone (alt):
0737159092
Division:
Division of Intelligent Future Technologies
Research groups:
Biomedical Engineering
Intelligent Systems
Web:
Official university homepage



Mobyen Uddin Ahmed is Senior Lecturer/Assistant Professor in Computer Science and Artificial Intelligence at Intelligent Systems group and a member of ESS-H - Embedded Sensor Systems for Health Research Profile. Mobyen has more than 100 scientific publication and more than 1016 citations.

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

He is involved in AI releted research and development since 2005. He is currently involved with several national and H2020 projects within AI- related area.

His research focuses on developing intelligent systems in medical and industrial applications. I am trying to invent adaptive methods, techniques to develop intelligent systems for IOT- based data analytic environment. Current research interest includes deep learning, case-based reasoning, datamining, fuzzy logic and other machine learning and machine intelligence approaches for analytics specially in Big data analytics.



Available theses

Feature Selection through Artificial Intelligence for EEG Signal Classification
A Decision Support System for medical diagnosis using Data Mining and Machine Learning
Activity monitoring in daily life using Shimmer sensing
An intelligent system for driver cognitive load detection using eye tracking data
Correlation analysis among EEG, EOG and EMG signals for identification of ocular and muscle activities
Data-driven actors modelling for road transportation
Data-driven Modelling on Powered Two Wheelers using Machine Learning
Deep Learning based Eye Tracking and Head Movement Detection
Detect drug abuse by AI processed eye movement data from a smart phone film
GameAlyzer - a wearables and AI based system to monitor gambling and gaming
Human Emotion Detection using Deep Learning
Machine learning based pedestrian event monitoring using IMU and GPS
Non-Contact Intelligent System to monitor driver’s alcoholic state using Biological Signals
Smart Mirror to monitor Health Status using Biological Signals

[Show all publications]

[Google Scholar author page]

Latest publications:

Quality Index Analysis on Camera-based R-peak Identification Considering Movements and Light Illumination (Jun 2018)
Mobyen Uddin Ahmed, Hamidur Rahman, Shahina Begum
15th International Conference on Wearable, Micro & Nano technologies for Personalized Health (pHealth2018)

Internet of Things (IoT) Technologies for HealthCare (Mar 2018)
Mobyen Uddin Ahmed, Shahina Begum, Jean-Baptiste Bastel
4th EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'17)

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

Cloud-based Data Analytics on Human Factor Measurement to Improve Safer Transport (Nov 2017)
Mobyen Uddin Ahmed, Shahina Begum, Carlos Alberto Catalina , Lior Limonad , Bertil Hök , Gianluca Di Flumeri
4th EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'17)

Run-Time Assurance for the E-care@home System (Nov 2017)
Mobyen Uddin Ahmed, Hossein Fotouhi, Uwe Köckemann , Maria Lindén, Ivan Tomasic, Nicolas Tsiftes , Thiemo Voigt
4th EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'17)

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

PhD students supervised as assistant supervisor:

Hadi Banaee (former)
Hamidur Rahman
Mohammed Ghaith Altarabichi
Shaibal Barua

MSc theses supervised (or examined):
Thesis TitleStatus
available
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 Shimmer sensing available
An intelligent system for driver cognitive load detection using eye tracking data available
Correlation analysis among EEG, EOG and EMG signals for identification of ocular and muscle activities available
Data-driven actors modelling for road transportation available
Data-driven Modelling on Powered Two Wheelers using Machine Learning available
Deep Learning based Eye Tracking and Head Movement Detection available
Detect drug abuse by AI processed eye movement data from a smart phone film available
GameAlyzer - a wearables and AI based system to monitor gambling and gaming available
Human Emotion Detection using Deep Learning available
Machine learning based pedestrian event monitoring using IMU and GPS 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 in progress
Test Oracle Automation with Machine Learning: A Feasibility Study in progress
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