AI in Analog Circuit Design: Emerging Trends and Innovations
IBM T. J. Watson Research Center
Time: 2025-04-23, 12:00 - 13:00 ET
Location: Olsson 105 and Zoom
Abstract The automation of analog circuit design is rapidly evolving with recent advancement of AI/ML, especially large language models (LLMs). The demand for new algorithms in analog circuit design is driven by the need to handle increasing complexity and stringent design constraints in advanced technology nodes. Traditional design methods, which rely heavily on manual iterations, are often time-consuming and limited in their ability to explore the full design space. This talk will explore how recent advances in AI/ML are transforming the analog EDA landscape, enabling more efficient and innovative design processes. We will discuss recent breakthroughs in ML-driven approaches for analog circuit design, including topology generation, performance optimization, and design space exploration.
Bio Xin Zhang is a Research Manager at the IBM T. J. Watson Research Center at Yorktown Heights, New York, and the MIT-IBM Watson AI Lab at Cambridge, Massachusetts. He is also an Adjunct Professor with the Department of Electrical Engineering, Columbia University, in New York city.
He has served as a TPC member for several top conferences including ISSCC, DAC, VLSI and APEC. He is also a Technical Advisory Board chair of the Semiconductor Research Corporation (SRC) and SMART USA. His research interests include analog circuit design, thermal solutions, system integration, and AI-based circuit design automation.