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. His current research in trustworthy AI with several ongoing project. 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.
90 test participants are required: click here
Journal Editors:
Sustainability Journal, IF:3.88, "Interpretable and Explainable AI Applications"
Sensors Journal, IF: 3.84, "Deep Learning in Biomedical Informatics and Healthcare"
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.
90 test participants required: click here
A Case Study on Ontology Development for AI Based Decision Systems in Industry (Jul 2023) Ricky Stanley D Cruze , Mobyen Uddin Ahmed, Marcus Bengtsson, Peter Funk, Rickard Sohlberg Dr H.C., Atiq Ur Rehman 7th International Congress and Workshop on Industrial AI and eMaintenance (IAI)
Artificial Intelligence in Predictive Maintenance: A Systematic Literature Review on Review Papers (Jul 2023) Md Rakibul Islam , Shahina Begum, Mobyen Uddin Ahmed 7th International Congress and Workshop on Industrial AI and eMaintenance (IAI)
Cognitive Digital Twin in Manufacturing: A Heuristic Approach (Jun 2023) Atiq Ur Rehman, Mobyen Uddin Ahmed, Shahina Begum 19th International Conference on Artificial Intelligence Applications and Innovations (AIAI2023)
Explaining the Unexplainable: Role of XAI for Flight Take-Off Time Delay Prediction (Jun 2023) Waleed Reafee Sbu Jmoona, Mobyen Uddin Ahmed, Mir Riyanul Islam, Shaibal Barua, Shahina Begum, Ana Ferreira , Nicola Cavagnetto 19th International Conference on Artificial Intelligence Applications and Innovations (AIAI2023)
Quantitative Performance Analysis of Machine Learning Model from Discrete Perspective: A CaseStudy of Chip Detection in Turning Process (Mar 2023) Sharmin Sultana Sheuly, Mobyen Uddin Ahmed, Shahina Begum 15th International Conference on Agents and Artificial Intelligence (ICAART2023)
A Systematic Literature Review on Multimodal Machine Learning: Applications, Challenges, Gaps and Future Directions (Mar 2023) Arnab Barua, Mobyen Uddin Ahmed, Shahina Begum Journal of IEEE Access (IEEE-Access)
Arnab Barua
Hamidur Rahman (former)
Mir Riyanul Islam
Sharmin Sultana Sheuly
Hadi Banaee (former)
Md Rakibul Islam
Mohammed Ghaith Altarabichi (former)
Shaibal Barua (former)