Can Artificial Intelligence and Data redefine engineers?--Transdisciplinary revolution in Engineering Education

The integration of artificial intelligence and big data analytics is reshapingengineering education, revealing differentiated institutional responsestotechnological convergence. Through transdisciplinary case studies of ZhejingUniversity (ZJU) and the University of California, Berkeley (UCB), this researchexamines paradigm evolution through three structural dimensions: knowledgereconstruction, organizational innovation, and ecosystemsupport. Twoimplementation paradigms emerge: ZJU's AI-centric model adopts a top-downtransformation by integrating strategic capabilities, whereas UCB's data-drivenapproach evolves bottom-up, leveraging existing infrastructure tomediateinstitutional change. The study conclusively demonstrates that transdisciplinaryeducation, driven by AI's capability for vertical knowledge integration and data'srolein horizontal competency expansion, redefines engineers as adaptive sociotechnical synthesizers -- directly answering the central inquiry of technological reconfigurationin engineering education.