Builder

Shangyan Zhou

Shangyan Zhou is an AI infrastructure builder whose work connects large language models with the systems behind training and inference. He graduated from Peking University in 2020 and spent three years at High-Flyer before joining DeepSeek. He coauthored the DeepSeek LLM, DeepSeek-V2, DeepSeek-V3 and DeepSeek-R1 papers, plus DeepEP, an expert-parallel communication library. His 2025 work also examines the hardware and infrastructure behind DeepSeek-V3 and R1. As of October 2026, he is an infrastructure developer at DeepSeek.

Now at
DeepSeek
Works
19
Badges

Publication numbers from OpenAlex, as of 22 October 2026. Citations and h-index are hidden because this OpenAlex record may be incomplete or mix in other authors.

Timeline

  1. 2020

    Peking University graduation

    He graduates from Peking University in 2020.

  2. January 2024

    DeepSeek LLM

    In January 2024, he coauthors DeepSeek LLM, a paper that studies scaling laws for open-source models at 7B and 67B sizes. The team trains its chat models with supervised fine-tuning and direct preference optimization.

  3. May 2024

    DeepSeek-V2 architecture

    In May 2024, he coauthors DeepSeek-V2, a 236-billion-parameter mixture-of-experts model with 21 billion active parameters per token. Its architecture combines Multi-head Latent Attention with DeepSeekMoE for efficient inference and economical training.

  4. December 2024

    DeepSeek-V3 Technical Report

    In December 2024, he coauthors the DeepSeek-V3 technical report, which presents a 671-billion-parameter mixture-of-experts model with 37 billion active parameters per token. The model trains on 14.8 trillion tokens.

  5. January 2025

    DeepSeek-R1 reasoning model

    In January 2025, he coauthors DeepSeek-R1, which uses reinforcement learning to develop reasoning abilities such as self-reflection, verification and dynamic strategy adaptation. The method uses no human-labeled reasoning trajectories.

  6. January 2025

    Infrastructure work at DeepSeek

    By January 2025, he works as a DeepSeek infrastructure developer. Before joining DeepSeek, he spends three years at High-Flyer, Liang Wenfeng's hedge fund.

  7. 2025

    DeepEP and infrastructure analysis

    In 2025, he coauthors DeepEP, an efficient expert-parallel communication library. He also coauthors a study of DeepSeek-V3 and R1, analyzing their architecture, AI infrastructure and hardware choices.

  8. As of October 2026

    Infrastructure developer at DeepSeek

    As of October 2026, he is an infrastructure developer at DeepSeek.

Career

  1. NowDeepSeekInfrastructure developer

Education

  1. 2020Peking University

Sources and credits

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  1. Deepseek's Liang Wenfeng hires graduates over "AI Wizards" efinancialcareers.com.au. Checked 20 October 2026.
  2. DeepSeek LLM: Scaling Open-Source Language Models with Longtermism arxiv.org. Checked 20 October 2026.
  3. DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model arxiv.org. Checked 20 October 2026.
  4. DeepSeek-V3 Technical Report arxiv.org. Checked 20 October 2026.
  5. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning arxiv.org. Checked 20 October 2026.
  6. Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures arxiv.org. Checked 20 October 2026.
  7. DeepEP: an efficient expert-parallel communication library github.com. Checked 20 October 2026.
  8. DeepSeek AI | The Org theorg.com. Checked 20 October 2026.