Yuping Fan

Background

About Yuping Fan

I am a Research Scientist specializing in Artificial Intelligence (AI), Machine Learning (ML), and High-Performance Computing (HPC). With a Ph.D. in Computer Science, my work focuses on AI/ML-driven and reinforcement learning (RL)-driven scheduling solutions and system optimization for large-scale computing systems. At Meta, I developed algorithms that significantly enhanced load balancer efficiency, reduced resource consumption, and improved video call quality across Meta platforms. At Argonne National Laboratory, my research centered on applying deep reinforcement learning (RL) and ML techniques to optimize HPC workload scheduling, performance efficiency, and system utilization. My work has been published in top-tier conferences (IPDPS, HPDC, SC, etc.), contributing to advancements in AI-driven HPC system optimization. Expertise: HPC | AI | ML | Reinforcement Learning | Parallel Computing Industry & Research Experience: Meta | Argonne National Laboratory | Ph.D. in AI-Driven HPC Publications & Contributions: ACM, and Supercomputing (SC) Conferences I am passionate about driving cutting-edge AI/ML solutions for HPC system optimization. I am always open to innovative AI-HPC opportunities. Let’s connect and explore the future of AI in HPC!