Keynote 1
AI Meets Chips and Packaging: From Prediction to Generation

David Z. Pan, University of Texas at Austin

AI is reshaping electronic design automation (EDA), enabling new approaches to performance prediction, design optimization, and design generation. This talk will offer a broad perspective on AI for EDA, with an emphasis on analog/RF design, where accurate modeling and computationally intensive simulation present compelling opportunities for learning-based methods. It will explore the emerging roles of large language models and agentic AI in design reasoning and tool orchestration. Examples spanning circuit synthesis, stack-up optimization, and PCB routing will highlight the complementary roles of AI/ML and constrained optimization. The talk will conclude with opportunities and challenges for integrating these capabilities toward trustworthy AI-driven chip–package co-design.

Prof. David Z. Pan is the Silicon Labs Endowed Chair Professor at the Department of Electrical and Computer Engineering, The University of Texas at Austin. His research interests include design automation for digital/analog/RF ICs and advanced packaging, synergistic AI/IC co-optimizations, and design/system and technology co-optimization. He has published over 550 technical papers and 10 US patents. He has served in many editorial boards and conference committees, including General Chair of DAC 2027 and ICCAD 2019. He has received many awards, including SRC Technical Excellence Award, Nvidia Research Faculty Fellow, over 20 Best Paper Awards from premier EDA/chip/AI venues, among others. He has graduated over 60 PhD students and postdocs who are now holding key academic and industry positions. He is a Fellow of IEEE, ACM, and SPIE.