Anna Goldie

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About

Anna Goldie is a leading researcher at the intersection of artificial intelligence and computer systems design, with a primary focus on using machine learning to optimize hardware and software infrastructure. Her most impactful work centers on applying reinforcement learning to placement optimization—a critical challenge in chip design where billions of components must be arranged to maximize performance and energy efficiency. As a key member of Google Brain’s Machine Learning for Systems team, Goldie has pioneered AI-driven approaches that fundamentally transform how computer chips and systems are architected. Her 2021 paper on reinforcement learning for placement optimization has garnered significant attention, laying the groundwork for a new paradigm where AI directly shapes the physical design of processors. Beyond chip design, her research extends to broader systems optimization, including compiler improvements and resource management. Goldie’s work exemplifies a visionary approach: using AI not just as an application but as a tool to redesign the very hardware that powers modern artificial intelligence. Her contributions are helping to create a virtuous cycle where smarter chips enable more powerful AI, which in turn designs even better chips.