Mobyen Uddin Ahmed, Senior Lecturer

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 100+ scientific publication and more than 1134 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 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

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Latest publications:

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)

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)

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)