Wei Shiung Liew

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About

Wei Shiung Liew is an AI researcher whose work sits at the intersection of explainable artificial intelligence (XAI), autonomous systems, and human-robot interaction. His research addresses one of the most pressing challenges in modern AI: building trustworthy, transparent systems that humans can meaningfully understand and rely upon. Liew's most influential contribution is his comprehensive review of explainable goal-driven agents and robots, a work that has garnered 66 citations and stands as a significant reference for researchers grappling with the "black box" limitations of deep learning neural networks. By systematically surveying how autonomous agents and robots — from self-driving cars to service robots — can be designed to explain their decision-making, Liew has helped lay a conceptual foundation for next-generation interpretable AI systems. His earlier work on measuring trust in human-robot interaction through interactive dialogs further demonstrates his commitment to understanding the nuanced psychological and communicative dimensions of human-machine relationships. For students and researchers exploring responsible AI, autonomous systems, or cognitive robotics, Liew's scholarship offers both a rigorous technical framework and a humanistic perspective on making AI systems genuinely accountable.