Chunyang Feng

Predictive & Generative AI: Transforming EDA Physical Design

Dr. Chunyang Feng
VP of R&D, Giga Design Automation

Abstract

As advanced semiconductor nodes push EDA physical design complexity to new heights, AI emerges as a critical solution. Predictive and generative AI are redefining EDA physical design workflows to address this escalating complexity. Predictive AI models forecast timing risks early in the design cycle, enabling proactive optimization and reducing iterative loops. Generative AI, meanwhile, streamlines traditionally labor-intensive processes and accelerates the path from design finalization to production. This session explores how predictive and generative AI are changing the face of RTL-to-GDS automation, thereby reducing iterations and increasing efficiency.

Speaker's Bio

Dr. Feng holds a Ph.D. in Microelectronics and Solid-State Electronics from Fudan University. Currently serving as Vice President of Shenzhen Giga Design Automation Co., Ltd., he leads the R&D of the digital sign-off tools and AI-related products.

Prior to joining Shenzhen Giga Design Automation, Dr. Feng worked at the R&D Center of Synopsys Shanghai, where he participated in the development of digital EDA tools for placement and routing, static timing analysis, and other key areas. He also served as a researcher at the Artificial Intelligence Research Center of Duke Kunshan University, bridging academic insights with practical applications. He has over 16 years of industry experience in the VLSI domain.

Alex Song

Thoughts in Edge AI design and the role of AI agentic in AI chip development

Dr. Alex Song
Head of IC R&D Operations, UNISOC

Abstract

The rapid evolution of AI in the recent years, motivates more and more fabless design companies to explore the edge AI chip design in the AI inference territory, and the market is predicted to be growing explosively in the next few years. As the industry leader in telecommunication, and the top fabless design company in China, UNISOC has unique strength and competitive edge designing Edge AI chips. Dr Song will focus on the power efficiency aspect of edge AI chip design, which cornerstones the core competitive advantage of the product. The quick adoption of AI agentic in the chip design flow has proved its value in terms of accelerating the design process, as well as improving the design quality. Dr Song will also discuss his understanding of the chemistry between AI agentic and design design flow, and the highlights of AI agentic practices in UNISOC.

Speaker's Bio

Dr Song is currently heading the IC R&D operation of UNISOC, responsible of designing a wide range of ASIC product from high performance mobile processors, IOT devices, and display TV SoCs etc. His prior experiences of more than 20 years in the industry also includes technical management positions at Hisilicon, ST microelectronics, and many other companies. Dr Song holds Ph.D. degree in microelectronics and solid-state from Fudan University.

Sze SiuFung-Keith

AI for Preventive Wellness: Building the Next Generation of Wearable Health Intelligence

Mr. Sze SiuFung-Keith
Senior Director of Software R&D, Ninenovo

Abstract

This talk explores how AI can transform wearable health products from simple data trackers into proactive wellness intelligence systems. By understanding each user’s personal health patterns, AI can help identify meaningful changes, explain what they may indicate, and provide practical micro-actions for daily improvement. The presentation will discuss how wearable devices and AI can work together to support preventive wellness, long-term behavior change, and a more personalized health experience.

Speaker's Bio

Sze SiuFung-Keith serves as Senior Director of Software Research and Development. He has extensive professional experience in wearable technology, artificial intelligence, and the research and development of intelligent health products. He focuses on empowering consumer wearable devices with cutting-edge AI algorithms to enhance personal health management systems.

With in-depth insights into the full lifecycle development of wearable health intelligence products, Sze SiuFung-Keith has long been dedicated to exploring the integration of artificial intelligence with preventive wellness scenarios. He leads the technical team in iterating core health data analysis frameworks and is committed to building more accurate, personalized, and proactive intelligent health perception systems for end users.