Joyce Xu

Joyce Xu

Engineer @ Paces

About Joyce Xu

Joyce Xu is an engineer with extensive experience in artificial intelligence and machine learning. She has worked for notable organizations such as DeepMind, The New York Times, and Replica, and advocates for open learning and research in the AI/ML community.

Current Position at Paces

Joyce Xu has been working as an Engineer at Paces since 2023. In this role, she applies her expertise in engineering and machine learning to contribute to the company's projects. Her current position reflects her ongoing commitment to advancing technology and innovation in the engineering field.

Previous Experience in AI and Machine Learning

Joyce Xu has held various positions in the AI and machine learning sectors. She worked as an AI Fellow at UnifyID for two months in 2019 and as a Machine Learning Intern at Volley for two months in 2016. Additionally, she served as a Research Engineering Intern at DeepMind in 2018 for three months, focusing on multi-agent reinforcement learning. Her experience includes developing visualization and analysis tools for DeepMind's research platform.

Educational Background in Computer Science

Joyce Xu studied Computer Science at Stanford University, where she earned her Bachelor's degree. Her education provided a strong foundation in computer science principles, which she has applied throughout her career in various engineering and research roles.

Contributions to Open Learning and Research

Joyce Xu advocates for open learning, open research, and open source within the AI and machine learning community. She has extended an open-source machine learning library for the functional programming community, demonstrating her commitment to collaborative and accessible research practices.

Public Speaking and Publications

Joyce Xu has been invited to speak at conferences that focus on data science and machine learning. Her writings on deep learning have been featured on several platforms, including Hacker News, KDnuggets, AITopics, The Startup Grind, and Towards Data Science, showcasing her engagement with the broader tech community.

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