{
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  "updatedAt": "2026-10-02T10:43:21Z",
  "site": {
    "name": "Chijun Sima",
    "title": "Chijun Sima",
    "url": "https://www.chijunsima.com/",
    "description": "Chijun Sima — CS PhD student at UT Austin (ML for systems, systems for ML). Co-first author of Ekko (OSDI '22). LLVM developer with commit access.",
    "language": "en",
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  "person": {
    "name": "Chijun Sima",
    "givenName": "Chijun",
    "familyName": "Sima",
    "jobTitle": "Computer Science PhD student",
    "subtitle": "",
    "affiliation": {
      "name": "The University of Texas at Austin",
      "department": "Department of Computer Science",
      "url": "https://www.cs.utexas.edu/"
    },
    "location": "Austin, Texas, USA",
    "advisors": [
      {
        "name": "Chenfeng Xu",
        "url": "https://www.chenfengx.com",
        "title": "Assistant Professor",
        "affiliation": "The University of Texas at Austin",
        "department": "Department of Computer Science"
      },
      {
        "name": "Aditya Akella",
        "url": "https://www.cs.utexas.edu/~akella/",
        "title": "Professor & Regents Chair",
        "affiliation": "The University of Texas at Austin",
        "department": "Department of Computer Science"
      }
    ],
    "researchInterests": [
      "Machine learning for systems",
      "Systems for machine learning"
    ],
    "summary": "Computer Science PhD student at The University of Texas at Austin, working on machine learning for systems and systems for machine learning. Co-first author of Ekko (OSDI 2022). LLVM developer with commit access.",
    "email": "simachijun@gmail.com",
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  "education": [
    {
      "period": "Aug 2026 – Present",
      "startDate": "2026-08",
      "endDate": null,
      "degree": "PhD in Computer Science",
      "school": "The University of Texas at Austin",
      "schoolUrl": "https://www.cs.utexas.edu/",
      "detail": "Department of Computer Science."
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      "period": "Sep 2016 – Jun 2020",
      "startDate": "2016-09",
      "endDate": "2020-06",
      "degree": "B.Eng. in Computer Science and Technology (Innovation Class)",
      "school": "South China University of Technology",
      "schoolUrl": "https://www.scut.edu.cn",
      "detail": "GPA 3.85 / 4.00 · Rank 1 / 28"
    }
  ],
  "publications": [
    {
      "id": "ekko-osdi-2022",
      "title": "Ekko: A Large-Scale Deep Learning Recommender System with Low-Latency Model Update",
      "venue": "OSDI '22",
      "venueFull": "16th USENIX Symposium on Operating Systems Design and Implementation",
      "year": 2022,
      "datePublished": "2022",
      "authors": [
        "Chijun Sima",
        "Yao Fu",
        "Man-Kit Sit",
        "Liyi Guo",
        "Xuri Gong",
        "Feng Lin",
        "Junyu Wu",
        "Yongsheng Li",
        "Haidong Rong",
        "Pierre-Louis Aublin",
        "Luo Mai"
      ],
      "authorLine": "Chijun Sima*, Yao Fu*, Man-Kit Sit, Liyi Guo, Xuri Gong, Feng Lin, Junyu Wu, Yongsheng Li, Haidong Rong, Pierre-Louis Aublin, Luo Mai",
      "url": "https://www.usenix.org/conference/osdi22/presentation/sima",
      "note": "* co-first author. Supervised by Luo Mai.",
      "summary": "Low-latency model update system for multi-terabyte deep learning recommendation models, achieving 2.4s update latency, 10,000x model-size scaling, and large production impact in WeChat."
    }
  ],
  "experience": [
    {
      "period": "Aug 2026 – Present",
      "startDate": "2026-08",
      "endDate": null,
      "role": "PhD Student in Computer Science",
      "subtitle": "",
      "organization": "The University of Texas at Austin",
      "organizationUrl": "https://www.cs.utexas.edu/",
      "location": "Austin, Texas, USA",
      "projects": [
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          "name": null,
          "note": null,
          "headline": null,
          "bullets": [
            "Advised by Chenfeng Xu and Aditya Akella."
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      "startDate": "2020-07",
      "endDate": "2026-08",
      "role": "Senior Software Development Engineer",
      "subtitle": "",
      "organization": "Tencent's WeChat division",
      "organizationUrl": "https://www.tencent.com",
      "location": "Guangzhou, China",
      "projects": [
        {
          "name": "Ekko: low-latency model update for multi-terabyte DLRMs",
          "note": "published in part as OSDI '22",
          "headline": "2.4 s model-update latency and 10,000× model-size scaling for multi-terabyte recommendation models; serves 1 B+ users daily in WeChat.",
          "bullets": [
            "Problem. Scaling DLRMs improved offline accuracy but degraded online engagement; root cause: stale models from increased model-update latency.",
            "Key idea. Co-designed deployment mechanisms with model-aware policies (compressed update dissemination, accuracy-aware scheduling, SLO-aware placement, safe rollback).",
            "Technical contributions. WAN bandwidth −92 %, machine cost −49 %, 2.4 s model-update latency; 10,000× model-size scaling (GB → tens of TB).",
            "Outcomes. Core techniques published as OSDI '22 (co-first author). Deployed in WeChat recommendation stacks, serves 1 B+ users daily. Official WeChat blog reports +40 % DAU and +87 % total VV over six months after full adoption (alongside product iteration and operations)."
          ]
        },
        {
          "name": "Data and feature platform: safe, scalable pipelines",
          "note": null,
          "headline": "WebAssembly-based runtime with in-process isolation; data movement reduced up to 1,200× on representative workloads.",
          "bullets": [
            "Problem. Modern feature pipelines are long and increasingly multimodal; cross-process operator composition creates high overhead and expensive data movement.",
            "Approach. WebAssembly-based runtime for in-process isolation (safety + resource constraints) and locality-aware operator placement near data sources.",
            "Outcome. Data movement reduced up to 1,200× on representative workloads; widely used within WeChat for data preparation."
          ]
        }
      ]
    },
    {
      "period": "2018 – Present",
      "startDate": "2018",
      "endDate": null,
      "role": "Developer (commit access)",
      "subtitle": "Google Summer of Code 2018",
      "organization": "LLVM",
      "organizationUrl": "https://llvm.org",
      "location": null,
      "projects": [
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          "name": null,
          "note": null,
          "headline": null,
          "bullets": [
            "Improved Semi-NCA performance and optimization pipeline; shipped in LLVM 9.0 (reported speedups up to 1,980× on real-world samples).",
            "Unified APIs on dominator trees; shipped in LLVM 7.0."
          ]
        }
      ]
    }
  ],
  "talks": [
    {
      "text": "Tencent's WeChat division, Shenzhen",
      "date": "Jun 2022"
    },
    {
      "text": "DataFun, Virtual",
      "date": "Aug 2022"
    },
    {
      "text": "TechBeat, Virtual",
      "date": "Sep 2022"
    }
  ],
  "reviewing": [
    "NeurIPS 2026",
    "BMVC 2026",
    "CVPR 2025"
  ],
  "awards": [
    {
      "text": "Tencent Technology Breakthrough Award (Gold Prize) — Project Lead, Ekko (internal highest technical honor)",
      "year": "2022"
    },
    {
      "text": "Bronze Medal, ACM-ICPC Asia Xi'an Regional Contest",
      "year": "2017"
    },
    {
      "text": "Second Prize, 15th China Collegiate Programming Contest (Guangdong Division, out of 177 teams)",
      "year": ""
    }
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      "href": "https://www.usenix.org/conference/osdi22/presentation/sima"
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