Key research thrusts within the rubric of transdisciplinary systems engineering and transdisciplinary engineering education

• Intelligent Digital Twinning - creating living, autonomous and adaptive counterpart to a physical system with the ability to monitor, analyze, and guide the behavior of the physical system; application domains: manufacturing, Model Based Systems Engineering

• Augmented Intelligence and Human-AI Teaming – exploiting AI and ML in the role of a partner with the ability to enhance human performance, amplify human capabilities, and make human-AI teaming effective

• Green Learning – a subfield of sustainable AI concerned with minimizing the environmental footprint of AI and ML algorithms in real-world applications by reducing computational complexity, training time, and carbon emissions

• Interactive Storytelling in Virtual Worlds – exploiting causal narrative execution in virtual worlds to experience system failures and environmental disruptions as dramatic turning points during interactive story execution, and provide branching within stories for counterfactual analysis

• AI-aided, Digital Twin-enabled Model Based Systems Engineering – exploiting both AI/ML and digital twinning to realize dynamic Verification and Validation Capability and increase reach of MBSE into the later stages of the system life cycle.