Key contributions in Robotic AI and Automation include spearheading AI-driven automation initiatives in semiconductor manufacturing, focusing on leading a specialized team in Robotic AI and Automation to optimize production workflows; developing and deploying AI-powered robotic systems to enhance efficiency and precision; pioneering automation strategies that reduced operational costs and improved throughput; integrating cutting-edge automation technologies across cross-functional teams and manufacturing facilities; advancing deep learning defect inspection techniques, including defect detection, classification, segmentation, and root cause analysis (RCA) to enhance accuracy and reliability; mentoring engineers in AI and automation, fostering a culture of innovation and technical excellence.
Research Experience
Before transitioning to academia, he served as a Data Scientist and Team Lead at Taiwan Semiconductor Manufacturing Company (TSMC), where he worked closely with Foundry Engineers to tackle complex data analytics challenges. His research spanned multiple domains, including defect inspection and yield prediction, leveraging state-of-the-art deep learning techniques to enhance semiconductor manufacturing processes.
Background
His research primarily focuses on Computer Vision and Robotic AI, with a strong emphasis on enhancing intelligent manufacturing and automations. He explores various domains, including Generative Models, 3D/4D Representation, and Large Multimodal Models, to advance AI’s role in augmenting human ingenuity and industrial innovation.
Miscellany
He is actively seeking passionate and motivated graduate and doctoral students who share a keen interest in exploring this captivating research domain. If you’re enthusiastic about investigating the intersection of AI and creativity, he wholeheartedly encourages you to reach out to him directly or utilize the personalized assistant available as a chatbot.