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 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)
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)
| Partner | Type |
|---|---|
| Ericsson AB | Industrial |
| Volvo Construction Equipment AB | Industrial |
