Trust_Gen_Z:Trustworthy Generative AI for Advanced Industrial DigitaliZation
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The project will facilitate inspection, monitoring, optimization and maintenance of industrial equipment and machinery. However, implementing a multimodal framework in the industry faces a challenge: the absence of reliable AI methods that generate predictions while offering prescriptive decisions. While the use of gAI looks promising for this task, there are significant gaps in current explainable AI (XAI) methods, which limit their applicability to prescriptive analytics. Trust_Gen_Z will address these challenges and support prescriptive analysis to advance digitization in the automotive and telecom industries. The strong consortium, which consists of a mix of industry (Ericsson and Volvo Construction Equipment), SME (MainlyAI) and academia (Mälardalen University), ensures research excellence in the project and contributes to Sweden's industrial development.
| First Name | Last Name | Title |
|---|---|---|
| Mobyen Uddin | Ahmed | Professor |
| Shahina | Begum | Professor |
| Shaibal | Barua | Senior Lecturer |
Enhancing Industrial AI Usability Through Human-AI Interaction (Jul 2026) Marcus Hammarström , Liam Burberry Gahm , Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum, Emmanuel Weiten , Daniel Aurel 28th International Conference on Computer and Information Technology (ICCIT25)
An End-to-End Explainable Fault Prediction Pipeline for Embedded Test Systems (Jul 2026) Md Motaher Hossain Bhuiyan, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum 28th International Conference on Computer and Information Technology (ICCIT25)
Bias-Aware Generative XAI for Sustainable Air Traffic Control: A Methodological Framework with Predictive Telemetry (Jun 2026) Mobyen Uddin Ahmed, Christophe Hurter , Shaibal Barua, Shahina Begum, Pietro Aricò , Nicola Cavagnetto International Conference on Artificial Intelligence, Automation and Control Technologies (AIACT 2026)
Explainable Hierarchical Self-Supervised Learning Framework for Intelligent Fault Discovery (Jun 2026) Md Rakibul Islam , Shahina Begum, Mobyen Uddin Ahmed International Conference on Artificial Intelligence, Automation and Control Technologies (AIACT 2026)
Explainable Quantum Machine Learning Concepts for Trajectory Optimization in Air Traffic Management (May 2026) Shahina Begum, Shaibal Barua, Mobyen Uddin Ahmed, Henri de Boutray , Christophe Hurter International Conference on Modern Artificial Intelligence and Data Science Systems (MAIDSS26)
Quantum Machine Learning for Optimisation: A Domain Focused Survey (May 2026) Surya Teja Darbhamalla, Shahina Begum, Shaibal Barua, Mobyen Uddin Ahmed International Conference on Modern Artificial Intelligence and Data Science Systems (MAIDSS26)
| Partner | Type |
|---|---|
| Ericsson AB | Industrial |
| Volvo Construction Equipment AB | Industrial |
