Shiyang Chen / The Mind's Tape

Black-Square-and-Red-Square-Malevich-Kasimir-1915.jpg
Black Square and Red Square (1915) by Kasimir Malevich
  • I am a Ph.D. student at Rutgers University, focusing on High-Performance Computing. I am interested in the intersection of AI and HPC, particularly in the areas of large language models and graph neural networks. I will graduate at the end of 2025.
  • I have experience in developing large-scale systems for AI workloads, including GNN inference and LLM inference.
  • I have interned at several companies, including Amazon Web Services, ByteDance, and Microsoft, where I worked on various projects related to AI and HPC.
  • I am passionate about computation efficiency and have a strong interest in exploring new architectures and algorithms to improve the performance of AI systems.

You can find my CV here.

news

May, 2025 I joined xAI as a Member of Technical Staff.
Mar, 2025 My paper “Deal: Distributed End-to-End GNN Inference for All Nodes” is available on ArXiv. It proposes a set of systematic optimizations for end-to-end GNN offline inference.
Jan, 2025 I will serve as a reviewer in MLSys 2025.
Jan, 2025 I will serve as a reviewer in ICJNN 2025.
Dec, 2024 My paper “KVDirect: Distributed Disaggregated LLM Inference” is available on ArXiv. It proposes a solution for the KV cache transfer in PD disaggregated LLM inference. It leverages the GPU RDMA to tackle the inefficiency and limitation in existing solutions such as NCCL and UCX.

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