Mobyen Uddin Ahmed, Professor
Mobyen Uddin Ahmed is a 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 135+ scientific publication and more than 2213+ 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 projects ‘SimuSafe’; Artimation; and FitDrive; Also, ‘BrainSafeDrive’, a bilateral project between Italy and Sweden funded by VR and Several national projects i.e., Digicogs, adapt2030, CPMXai and ‘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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Machine Learning Based Digital Twin in Manufacturing: A Bibliometric Analysis and Evolutionary Overview (Jul 2022) Sharmin Sultana Sheuly, Mobyen Uddin Ahmed, Shahina Begum Applied Sciences- Computing and Artificial Intelligence(Special issue:Artificial Intelligence and Optimization in Industry 4.0) (applsci)
A Systematic Review of Explainable Artificial Intelligence in terms of Different Application Domains and Tasks (Jan 2022) Mir Riyanul Islam, Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum Applied Sciences - Computing and Artificial Intelligence (Special Issue: Explainable Artificial Intelligence (XAI)) (ApplSci XAI)
A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory (Jan 2022) Augustin Degas , Mir Riyanul Islam, Christophe Hurter , Shaibal Barua, Hamidur Rahman, Minesh Poudel , Daniele Ruscio , Mobyen Uddin Ahmed, Shahina Begum, Md Aquif Rahman, Stefano Bonelli , Giulia Cartocci , Gianluca Di Flumeri , Gianluca Borghini , Fabio Babiloni , Pietro Aricò Applied Sciences - Computing and Artificial Intelligence (Special Issue: Explainable Artificial Intelligence (XAI)) (ApplSci XAI)
Dilemmas in designing e-learning experiences for professionals (Dec 2021) Mobyen Uddin Ahmed, Ioanna Aslanidou, Jakob Axelsson, Shahina Begum, Leo Hatvani, Anders Olsson, Sebastian Schwede, Carina Sjödin, Jan Skvaril, Valentina Zaccaria 20th European Conference on e-Learning (ECEL)
Explainable Machine Learning to Improve Assembly Line Automation (Dec 2021) Sharmin Sultana Sheuly, Mobyen Uddin Ahmed, Shahina Begum, Michael Osbakk 4th International Conference on Artificial Intelligence for Industries (ai4i 2021)
Vision-Based Driver’s Cognitive Load Classification Considering Eye Movement Using Machine Learning and Deep Learning (Nov 2021) Hamidur Rahman, Mobyen Uddin Ahmed, Shaibal Barua, Peter Funk, Shahina Begum Special Issue on Deep Learning in Biomedical Informatics and Healthcare (Sensors)
Arnab Barua
Hamidur Rahman (former)
Mir Riyanul Islam
Sharmin Sultana Sheuly
Hadi Banaee (former)
Md Rakibul Islam
Mohammed Ghaith Altarabichi (former)
Shaibal Barua (former)