Mobyen Uddin Ahmed, Associate Professor

E-mail:
mobyen.ahmed@mdh.se
Room:
U1-123
Phone:
+46-021-107369
Phone (alt):
0736620804
Division:
Division of Intelligent Future Technologies
Research groups:
Artificial Intelligence and Intelligent Systems
Biomedical Engineering
Web:
Official university homepage



Mobyen Uddin Ahmed is an Associate Professor in Artificial Intelligence/Computer Science at  Artificial Intelligence and Intelligent Systems group and a member of ESS-H - Embedded Sensor Systems for Health Research Profile. Mobyen has 100+ scientific publication and more than 1173 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 his 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

Mobyen is the co-applicant and project leader for MDH for the H2020 project ‘SimuSafe’; ‘BrainSafeDrive’, a bilateral project between Italy and Sweden funded by VR and a national project ‘InVIP’. He has been also involved in many other national and international projects , such as ecare@home, ESS-H, SafeDriver, PainOut, VDM, Prompt, FutureE, etc. He is one of the Principle Investigator of the research profile Embedded Sensor Systems for Health (ESS-H) at MDH.

 Mobyen has been selected twice (i.e. HealthyIoT2016, HealthyIoT2017) to be the general chair of an international conference ‘International Conference on IoT Technologies for HealthCare’. He has organized several other international conferences namely ICCBR2018, pHealth2015, ESS-HIoT2015.

Mobyen is involved in teaching and are responsible for courses Applied Artificial Intelligence, Project in intelligent embedded systems, and Databases. He is also involved in development and teaching for the course Machine Learning With Big Data (a distance course for industrial professionals), Deep learning for industrial imaging (coming), Predictive Data Analytics (coming), MooC course Ground Knowledge on Machine Learning (coming). Also, he is involved in the development of learning materials for AI and deep learning in the project Into DeeP.


Available theses

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
Deep learning to classify driving events using GPS data 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
Non-Contact Intelligent System to monitor driver’s alcoholic state using Biological Signals available
Smart Mirror to monitor Health Status using Biological Signals available


Mobyen is involved in AI and Machine Learning related research and development since 2005. He is currently involved with several national and H2020 projects within AI and ML related area.

His research focuses on developing intelligent systems in medical and industrial applications using multimodal machine learning and reasoning. He is trying to invent adaptive methods, techniques to develop intelligent systems for IOT- based data analytic environment.

His 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.

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Latest publications:

Non-contact Physiological Parameters Extraction using Facial Video considering Illumination, Motion, Movement and Vibration (May 2019)
Hamidur Rahman, Mobyen Uddin Ahmed, Shahina Begum
IEEE Transactions on Biomedical Engineering (TBME)

Drivers' Sleepiness Classification using Machine Learning with Physiological and Contextual data (Mar 2019)
Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum
First International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI' 2019)

Data Analysis on Powered Two Wheelers Riders’ Behaviour using Machine Learning (Mar 2019)
Mobyen Uddin Ahmed, Abderrahmane Boubezoul , Nils Göran Gustav Forsström , Nabaz Sherif , Daniel Stenekap , Stephane Espie , Anton Sundström , Rasmus Södergren
First International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI' 2019)

Supervised Learning for Road Junctions Identification using IMU (Mar 2019)
Mohammed Ghaith Altarabichi, Mobyen Uddin Ahmed, Shahina Begum
First International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI' 2019)

A Machine Learning Approach to Classify Pedestrians’ Event based on IMU and GPS (Jan 2019)
Mobyen Uddin Ahmed, Staffan Brickman , Alexander Dengg , Niklas Fasth , Marko Mihajlovic , Jacob Norman
International Conference on Modern Intelligent Systems Concepts (MISC'18)

A Vision based Indoor Navigation System for Individual with Visual Impairment (Jan 2019)
Mobyen Uddin Ahmed, Mohammed Ghaith Altarabichi, Shahina Begum, Fredrik Ginsberg , Robert Glaes , Magnus Östgren , Hamidur Rahman, Magnus Sörensen
International Conference on Modern Intelligent Systems Concepts (MISC'18)

PhD students supervised as assistant supervisor:

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

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
Deep learning to classify driving events using GPS data 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
Non-Contact Intelligent System to monitor driver’s alcoholic state using Biological Signals available
Remote monitoring of physiological parameters using facial images available
Smart Mirror to monitor Health Status using Biological Signals available
Applying artificial intelligence to identify drivers’ cognitive load based on correlation between EEG signals and driving behaviour signals in progress
Human Emotion Detection using Deep Learning in progress
Machine Learning applied on embedded system recordings 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
MACHINE LEARNING BASED PEDESTRIAN EVENT MONITORING USING IMU AND GPS finished
Multi-Sensor Information Fusion for Monitoring Driver’s Level of Performance finished
Online fuzzy case-based individual stress diagnosing system finished
Test Oracle Automation with Machine Learning: A Feasibility Study finished
Textual CBR system using domain specific ontology finished
Using NLP and context for improved search result in specialized search engines finished