Chang Guo

Biography

Chang Guo

I am a PhD Candidate in Computer Science at Arizona State University, advised by Prof. Zhichao Cao. Before joining ASU, I earned a B.E. in Automation and a B.B.A. in Business Administration from Tsinghua University.

My research focuses on indexing, caching, and storage systems for LLM inference and scientific computing. LegoIndex received the ACM HPDC 2025 Best Student Paper Award.

I am currently a Software Engineering Intern on the NVIDIA Dynamo team. I work on tiered KV cache management across GPU, CPU, and SSD.

News

  • Started as a Software Engineering Intern on the NVIDIA Dynamo team.
  • O3-LSM appeared at ACM SIGMOD 2026.[paper]
  • LegoIndex received the ACM HPDC 2025 Best Student Paper Award.[paper]
  • Mosaic-Cache appeared at ACM HotStorage 2025.[paper]
  • Started a research internship at ByteDance.
  • Our work on ZNS SSDs for persistent caching appeared at ACM HotStorage 2024.[paper]
  • CaaS-LSM appeared at ACM SIGMOD 2024.[paper]
  • SAS-Cache and Prophet appeared at IEEE MSST 2024.[SAS-Cache][Prophet]
  • Returned to Oak Ridge National Laboratory for a second research internship.
  • Started a research internship with the ADIOS2 team at Oak Ridge National Laboratory.
  • Started my PhD in Computer Science at Arizona State University.

Selected Research

LegoIndex architecture with a cell index and customizable multi-level in-cell indexes

[HPDC'25] LegoIndex: A Scalable and Modular Indexing Framework for Efficient Analysis of Extreme-Scale Particle Data[paper][ppt]

ACM HPDC 2025 Best Student Paper Award

Chang Guo, Ning Yan, Lipeng Wan, and Zhichao Cao

Mosaic-Cache architecture with overlap-aware partitioning, metadata management, fetch planning, and asynchronous merging

[HotStorage'25] Mosaic-Cache — Unlocking the Unusable: A Proactive Caching Framework for Reusing Partial Overlapped Data[paper][ppt]

Chang Guo, Norbert Podhorszki, Greg Eisenhauer, Zhiwen Xie, Scott Klasky, and Zhichao Cao

Experience

NVIDIA (Dynamo)

Software Engineering Intern

Santa Clara, CA
  • Defined backend configuration and publisher-relative locality contracts for vLLM native KV offloading. Separated storage type from deployment topology while preserving backward compatibility.
  • Built self-describing KV events across vLLM, Dynamo, and llm-d. Routed CPU and local storage placements into Dynamo's lower-tier KV index and made unsupported media fail closed.
  • Deduplicated replicated MLA KV across tensor-parallel ranks in shared CPU memory. At TP=N, this provides about N× the effective offload capacity and reduces D2H store traffic by N×.

ByteDance

Research Intern

San Jose, CA
  • Co-developed GPU-centric storage for LLM checkpointing and KV cache offloading, integrated with LMCache and vLLM.

Oak Ridge National Laboratory (ADIOS2)

Research Intern

Oak Ridge, TN
  • Built client-side caching for remote scientific data, including partial-overlap reuse and metadata indexing.
  • Developed Mosaic-Cache during the internship; the work appeared at ACM HotStorage '25 and was upstreamed through three merged ADIOS2 pull requests.

Caixin Data

Algorithm Engineer

Beijing, China
  • Built NLP pipelines for information extraction, topic modeling, and sentiment analysis over financial documents and business news.

Education

Arizona State University

PhD Candidate, Computer Science

Intelligent Data Infrastructure Lab; advisor: Prof. Zhichao Cao.

Tsinghua University

B.E. in Automation

Dual degree: B.B.A. in Business Administration.

Selected Open-Source Contributions

vLLM

Teaching

CSE 511: Data Processing at Scale

Teaching Assistant · Graduate-level

CSE 330: Operating Systems

Teaching Assistant · Undergraduate-level

Awards

Academic Service