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 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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ENHANCING EXPLAINABILITY, ROBUSTNESS, AND AUTONOMY: A COMPREHENSIVE APPROACH IN TRUSTWORTHY AI (May 2025) Mobyen Uddin Ahmed, Shahina Begum, Shaibal Barua, Abu Naser Masud, Gianluca Di Flumeri , Nicolò Navarin IEEE Symposium on Explainable, Responsible, and Trustworthy CI (IEEE CITREx)
In-Depth Analysis of Diverse Driver Behaviors using Hybrid Multimodal Machine Learning (Mar 2025) Mera Abudiab , Francisco Javier Pérez Núñez , Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum, Arnab Barua International Conference on Computer and Information Technology (ICCIT)
Advanced Hybrid Reasoning and Transfer Learning on Multimodal Data with Transformers (Feb 2025) Arnab Barua, Mobyen Uddin Ahmed, Shahina Begum Springer Nature Computer Science (SNCS)
Role of Multi-modal Machine Learning, Explainable AI and Human-AI Teaming in Trusted Intelligent Systems for Remote Digital Towers (Jan 2025) Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum, Waleed Reafee Sbu Jmoona, Ricky Stanley D Cruze , Alexandre Veyrie , Christophe Hurter 7th Artificial Intelligence and Cloud Computing Conference (AICCC2024)
Trust_Gen_Z: Trustworthy Generative AI for Advanced Industrial DigitaliZation (Oct 2024) Shahina Begum, Shaibal Barua, Mobyen Uddin Ahmed 7th Artificial Intelligence and Cloud Computing Conference (AICCC2024)
Chip Analysis for Tool Wear Monitoring in Machining: A Deep Learning Approach (Aug 2024) Atiq Ur Rehman, Tahira Salwa Rabbi Nishat, Mobyen Uddin Ahmed, Shahina Begum, Abhishek Ranjan Journal of IEEE Access (Access'18)
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)