ECE Seminar - Learning and Scientific Research in the Age of Artificial Intelligence
Supporting the below United Nations Sustainable Development Goals:支持以下聯合國可持續發展目標：支持以下联合国可持续发展目标：
Abstract: New application scenarios for artificial intelligence (AI) are constantly emerging. AI not only drives technological iterations but also reshapes industrial ecosystems. In the era of big data, the question arises: Do we still need to learn? The answer is a resounding yes. Not only must we learn, but we must also learn effectively. We should learn from the ancients and from big data, but we must avoid being trapped in information bubbles. This means that our learning today should be broader and more in-depth. When applying AI and big data, we are further required to master foundational knowledge in mathematics, physics, and chemistry. Only in this way can we use AI and big data tools efficiently and correctly!
Professor Yeh received his B.Eng. from Cheng Kung University, Taiwan, MS Degree in Applied Mathematics from Brown University, MS degree in Applied Mechanics from Columbia University and Ph D. in Composite Materials from University of Southern California respectively. He has served at California State University, Long Beach for over three decades, with research interests focusing on composite materials, fracture mechanics, and engineering failure analysis. Since 2003, he has traveled to and taught at various prestigious institutions in China, including the Qian Xuesen Mechanics Class at Tsinghua University in Beijing, the Graduate School of the Chinese Academy of Sciences, Beijing Institute of Technology, Beijing Mining University, Tongji University in Shanghai, and Sun Yat-Sen University in Guangzhou. Additionally, he has been invited to serve as a peer reviewer for academic journals such as the American Journal of Composite Materials, Engineering Fracture Mechanics, and the Journal of Applied Mechanics.