TRUSTY: TRUSTWORTHY INTELLIGENT SYSTEM FOR REMOTE DIGITAL TOWER

Overall, the goal of TRUSTY is to provide adaptation in the level of transparency to enhance the trustworthiness of AI-powered decisions in the context of remote digital towers (RDTs). While in an actual tower, operators have direct visual access to the taxiway and runway monitoring, the RDTs concept only provides such information through video transmission with a warning and the corresponding explanation. To deliver trustworthiness in an AI-powered intelligent system TRUSTY will consider several approaches, and they are listed:
•    ‘Self-explainable and Self-learning’ system for critical decision-making
•    ‘Transparent ML’ models incorporating interpretability, fairness, and accountability
•    ‘Interactive data visualization and multimodal human-machine interface/interactions (HMI), i.e., Graphical User Interface (GUI)’ for smart and efficient decision support
•    ‘Adaptive level of explanation’ regarding the user's cognitive state.
•    “HCAI” to enhance the trustworthiness of AI-powered systems.
•    “Human-machine collaboration (HMC) or Human-AI teaming (HAIT)” to consider user feedback to insure some computation flexibility and the users’ acceptability.

[Show all publications]

A Multimodal Approach for Enhancing Decision Support in Remote Digital Tower (Sep 2025)
Mobyen Uddin Ahmed, Shaibal Barua, Mir Riyanul Islam, Ricky Stanley D Cruze , Shahina Begum, Sara Kebir , Alexandre Veyrie , Christophe Hurter
2025 10th International Conference on Machine Learning Technologies (ICMLT 2025)

Integration of Explainable Artificial Intelligence and Multimodal Machine Learning for Drivers’ Fitness (Sep 2025)
Mobyen Uddin Ahmed, Arnab Barua, Mir Riyanul Islam, Shaibal Barua, Shahina Begum
International conference on Advanced Machine Learning and Data Science (AMLDS 25)

A Theoretical Probabilistic Framework for Explaining Generative AI (Sep 2025)
Shahina Begum, Shaibal Barua, Mobyen Uddin Ahmed, Mir Riyanul Islam
International conference on Advanced Machine Learning and Data Science (AMLDS 25)

Towards Sustainable AI Development: A Focus on Transparency and Explainability (Jul 2025)
Shahina Begum, Mobyen Uddin Ahmed, Mosarrat Farhana
2nd International Conference on Creativity, Technology, and Sustainability (CCTS)

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)

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)