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Explore how deep learning revolutionizes chip design in this keynote presentation delivered by UCLA Professor Jason Cong at KDD 2025. Discover the intersection of artificial intelligence and semiconductor engineering as Cong, a distinguished member of the National Academy of Engineering and recipient of the ACM Chuck Thacker Breakthrough Award, shares insights from his extensive research in VLSI circuits, customizable computing architectures, and FPGA synthesis. Learn about cutting-edge approaches to hardware design automation, the role of machine learning in optimizing chip performance, and how AI-driven methodologies are transforming traditional electronic design automation workflows. Gain understanding of novel architectures for domain-specific computing, high-level synthesis techniques, and the future of intelligent chip design tools. Drawing from his experience as co-founder of AutoESL (which developed the widely-used Vivado HLS tool) and his leadership of UCLA's Center for Domain-Specific Computing, Cong presents practical applications and theoretical foundations of applying deep learning to solve complex chip design challenges, making this essential viewing for researchers, engineers, and practitioners working at the convergence of AI and hardware design.
