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Research Interests

I study how principles of reliability, adaptability, and efficiency from engineered systems can inform the design of next-generation intelligent technologies. My work bridges materials science, energy systems, and physics-informed modeling with artificial and biological paradigms of intelligence. By integrating experiments, simulations, and AI-assisted analysis, I aim to develop strategies that enhance intelligent computation and hardware systems

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Intelligence of Materials

Transferring insights from materials and energy systems—such as stability, lifetime prediction, and dynamic modeling—into frameworks that guide robust and efficient intelligent system design.

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AI Contribution

Exploring the mechanisms of information processing and adaptation in natural and engineered systems. I focus on combining physics-based modeling with data-driven approaches to build scalable, reliable, and adaptive forms of intelligence.

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Manufacturing

Applying perception-driven intelligence to robotics and manufacturing by developing adaptive control, intelligent automation, and quality assessment frameworks that link sensing, computation, and production systems.

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