[30/09/2024] Yao Fu, a PhD student at the University of Edinburgh's School of Informatics, has been awarded the prestigious Rising Star in Machine Learning and Systems by the MLCommons Committee. This year’s Rising Stars cohort includes 41 junior researchers from 33 institutions globally. Selected from over 170 applicants, Yao is the sole recipient from the UK and one of three from Europe, the other two European students coming from ETH, Zurich. The 2024 Rising Start workshop was held in the NVIDIA HQ in Santa Clara, CA in July, where Yao presented his research. Yao is a third-year PhD student in Computer Science at The University of Edinburgh, supervised by Dr Luo Mai. His research lies at the intersection of machine learning and systems, focusing on performance and affordability. Recently, his work has centred on efficient serving systems for large language models, leading to two main projects: ServerlessLLM and the MoESys Leaderboard. He received his BE in Computer Science and Technology from Sun Yat-sen University in 2021. I am deeply honoured to be recognized as a rising star in Machine Learning and Systems by the MLCommons Committee. Attending the award event at Nvidia Headquarters was an inspiring experience, as I had the opportunity to engage with world-leading researchers in AI systems from academia and industry giants like Nvidia.This recognition is a major milestone in my research journey, highlighting the importance of making large language model (LLM) technology more accessible by lowering barriers of cost and complexity. It inspires me to continue exploring innovative serverless computing systems for emerging AI models.I am incredibly grateful for the unwavering guidance of my supervisor, Dr Luo Mai, and for the support from my collaborators. The School of Informatics is a unique place to conduct cutting-edge AI systems research, thanks to interdisciplinary collaboration opportunities with extraordinary researchers in both AI and computer systems. Yao Fu MLCommons ethos The industry nonprofit entity MLCommons was created by a consortium of companies to build a standardized set of benchmarks along with a standardized test methodology that allows different machine learning systems to be compared. It is built on a philosophy of open collaboration to improve AI systems. Through their collective engineering efforts with industry and academia MLCommons measure and improve the accuracy, safety, speed, and efficiency of AI technologies, helping companies and universities around the world build better AI systems that will benefit society. ML and Systems Rising Stars The ML and Systems Rising Stars is an initiative designed to identify a cohort of early-to-late-stage and recently graduated PhD students, as well as other researchers with a relevant background, to develop community, foster research and career growth, enable collaborations, and discuss career opportunities among the rising generation of researchers at intersections of machine learning and systems. Related links Link to MLCommons announcement Link to Yao Fu’s personal website Publication date 30 Sep, 2024
