PeopleofSuperintelligence

Researcher

Zijia Zhu

Zijia Zhu is an AI researcher whose name appears on DeepSeek technical reports about language models, reasoning and efficient inference. They coauthored the DeepSeek-V3 report in 2024, which described a 671-billion-parameter model trained on 14.8 trillion tokens. Their 2025 papers covered DeepSeek-R1's reinforcement-learning approach to reasoning and DeepSeek-V3.2's efficient reasoning and agent performance; DeepSeek-V4 added million-token contexts in 2026. As of October 2026, they are listed as a coauthor of DeepSeek-V4.1-Flash, a report on KV-cache compression.

Timeline

  1. December 2024

    DeepSeek-V3 technical report

    In December 2024, they coauthor the DeepSeek-V3 report, which describes a 671-billion-parameter mixture-of-experts model with 37 billion active parameters per token. Its training uses 14.8 trillion tokens.

  2. January 2025–September 2025

    DeepSeek-R1 reasoning report

    In January 2025, they coauthor the DeepSeek-R1 report, which shows that pure reinforcement learning can encourage reasoning abilities in language models. The September 2025 Nature article credits the authors with collecting and curating data, designing experiments and building the LLM training framework.

  3. December 2025

    DeepSeek-V3.2 technical report

    In December 2025, they coauthor DeepSeek-V3.2, a report on a model designed for high computational efficiency, reasoning and agent performance.

  4. April 2026

    DeepSeek-V4 million-token models

    In April 2026, they coauthor the DeepSeek-V4 report, which presents two mixture-of-experts models with context lengths of one million tokens.

  5. As of October 2026

    DeepSeek-V4.1-Flash KV-cache work

    As of October 2026, they are listed as a coauthor of DeepSeek-V4.1-Flash. Its September 2026 report describes cross-layer KV-cache reuse and FP4 caching to reduce cache size.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  2. The United States employs an estimated 48% of people shaping AIWe estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  3. 43% of living people shaping AI work outside their country of birthWe estimate that 43% of living people shaping AI work outside their country of birth (520 of 1,198 people with known birth and employment countries).
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionWe estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.

Sources and credits

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  1. DeepSeek-V3 Technical Report arxiv.org. Checked 20 October 2026.
  2. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning arxiv.org. Checked 20 October 2026.
  3. DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning nature.com. Checked 20 October 2026.
  4. DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models arxiv.org. Checked 20 October 2026.
  5. DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arxiv.org. Checked 20 October 2026.
  6. DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression arxiv.org. Checked 20 October 2026.
  7. DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression | alphaXiv alphaxiv.org. Checked 20 October 2026.