Mobyen Uddin Ahmed, Associate Professor
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 1460+ 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.
Ongoing conference, Advanced Artificial Intelligence & Robotics, ASPAI' 2020. 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 is responsible for courses Applied Artificial Intelligence, Project in intelligent embedded systems, and Databases. He is also involved in the development and teaching for the course Machine Learning With Big Data (a distance course for industrial professionals), Deep learning for industrial imaging, Predictive Data Analytics, 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.
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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, data mining, fuzzy logic and other machine learning and machine intelligence approaches for analytics especially in Big data.
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Analysis of Breakdown Reports using Natural Language Processing and Machine Learning (Aug 2021) Mobyen Uddin Ahmed, Marcus Bengtsson, Antti Salonen, Peter Funk International Congress and Workshop on Industrial AI (IAI2021)
Convolutional Neural Network for Driving Manoeuvre Identification based on Inertial Measurement Unit (IMU) and Global Positioning System (GPS) (Sep 2020) Mobyen Uddin Ahmed, Shahina Begum Frontiers in Sustainable Cities-Governance and Cities (Advances in Road Safety Planning) (Frontiers)
Machine Learning for Cognitive Load Classification – a Case Study on Contact-free Approach (Aug 2020) Mobyen Uddin Ahmed, Shahina Begum, Rikard Gestlöf , Hamidur Rahman, Johannes Sörman 16th International Conference on Artificial Intelligence Applications and Innovations (AIAI 2020)
A Novel Mutual Information based Feature Set for Drivers’ Mental Workload Evaluation Using Machine Learning (Aug 2020) Mir Riyanul Islam, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum, Pietro Aricò , Gianluca Borghini , Gianluca Di Flumeri Brain Sciences (Special Issue: Brain Plasticity, Cognitive Training and Mental States Assessment) (Brain Sci)
Artificial Intelligence, Machine learning and Reasoning in Health Informatics – Case Studies (Aug 2020) Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum Signal Processing Techniques for Computational Health Informatics (SPT)
Artificial Intelligence, Machine learning and Reasoning in Health Informatics – An Overview (Aug 2020) Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum Signal Processing Techniques for Computational Health Informatics (SPT)
Hamidur Rahman
Mir Riyanul Islam
Sharmin Sultana Sheuly
Hadi Banaee (former)
Mohammed Ghaith Altarabichi (former)
Shaibal Barua (former)