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 150+ scientific publication and more than 3080+ citations.
Mobyen on IVA list twice: 2022 and 2023
He is involved in research and development since 2005 after completing his M.Sc. in Computer Engineering (Specialization in Intelligent Systems, thesis) from Dalarna University, Sweden. He received his PhD (thesis) in Artificial Intelligence/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 main-applicant and project leader for for MDU for the H2020 projects ‘SimuSafe’; Artimation; TRUSTY 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 Machine Learning, Machine Learning Concepts, 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. Also, he is involved in the development of learning materials for AI and deep learning in the project Into DeeP.
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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 and HE projects within AI and ML related area.
His research focuses on developing intelligent systems in different application domains such as healthcare, road safety, air safety, industry 4.0, energy, and software application domains. He is using adaptive methods, algorithms and techniques to develop safe, and robust AI systems for increasing trustworthiness in AI systems that includes generative AI, AI Unification, XAI, human-centric AI, bias and fairness.
His current research also includes XAI, 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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Balancing Fairness: Unveiling the Potential of SMOTE-Driven Oversampling in AI Model Enhancement (May 2024) Md Alamgir Kabir , Mobyen Uddin Ahmed, Shahina Begum, Shaibal Barua, Md Rakibul Islam International Conference on Machine Learning Technologies (ICMLT)
Combining Ontology and Large Language Models to Identify Recurring Machine Failures in Free-Text Fields (Apr 2024) Marcus Bengtsson, Mobyen Uddin Ahmed, Ricky Stanley D Cruze , Peter Funk, Tomohiko Sakao , Rickard Sohlberg Dr H.C. THE 11th SWEDISH PRODUCTION SYMPOSIUM (SPS24)
Examining Decision-Making in Air Traffic Control: Enhancing Transparency and Decision Support Through Machine Learning, Explanation, and Visualization: A Case Study (Mar 2024) Christophe Hurter , Augustin Degas , Arnaud Guibert , Maelan Poyer , Nicolas Durand , Alexandre Veyrie , Ana Ferreira , Stefano Bonelli , Mobyen Uddin Ahmed, Waleed Reafee Sbu Jmoona, Shaibal Barua, Shahina Begum, Giulia Cartocci , Gianluca Di Flumeri , Gianluca Borghini , Fabio Babiloni , Pietro Aricò 16th International Conference Agents and Artificial Intelligence (ICAART2024)
iXGB: Improving the Interpretability of XGBoost using Decision Rules and Counterfactuals (Mar 2024) Mir Riyanul Islam, Mobyen Uddin Ahmed, Shahina Begum 16th International Conference Agents and Artificial Intelligence (ICAART2024)
Second-Order Learning with Grounding Alignment: A Multimodal Reasoning Approach to Handle Unlabelled Data (Feb 2024) Arnab Barua, Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum, Andrea Giorgi 16th International Conference Agents and Artificial Intelligence (ICAART2024)
Neurophysiological mental fatigue assessment for developing usercentred Artificial Intelligence as a solution for autonomous driving (Nov 2023) Andrea Giorgi , Vincenzo Ronca , Alessia Vozzi , Pietro Aricò , Gianluca Borghini , Rossella Capotorto , Luca Tamborra , Ilaria Simonetti , Simone Sportiello , Marco Petrelli , Carlo Polidori , Rodrigo Varga , Marteyn van Gasteren , Arnab Barua, Mobyen Uddin Ahmed, Fabio Babiloni , Gianluca Di Flumeri Frontiers in Neurorobotics (Front Neurorobot)
Arnab Barua
Hamidur Rahman (former)
Mir Riyanul Islam (former)
Sharmin Sultana Sheuly
Hadi Banaee (former)
Md Rakibul Islam
Mohammed Ghaith Altarabichi (former)
Shaibal Barua (former)