Research Areas

Defect-Aware Semiconductor Digital Twins

We develop defect-aware predictive digital twins for semiconductor materials and advanced packaging, leveraging advanced modeling and simulation to capture defect initiation, evolution, and their effects on performance and reliability.

Scientific Machine Learning

We develop scientific machine learning algorithms that integrate data-driven approaches with physics-based modeling to accelerate discovery, enhance prediction accuracy, and enable efficient solutions across diverse scientific and engineering domains.

Physical Intelligence for Robotics

We focus on the development of advanced algorithms and models for physical intelligence for robotics. By integrating multimodal perception (via Apple Vision Pro), natural language understanding, and intelligent manipulations on the Mobile ALOHA platform, we aim to achieve autonomous and intelligent execution of manipulation tasks in unstructured real-world environments.