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Biography

I am an assistant professor in the Department of Computer Science at Duke University. Before Duke, I was a postdoctoral researcher at UC Berkeley, working with Professor Ion Stoica. I completed my Ph.D. in the Paul G. Allen School of Computer Science and Engineering at University of Washington, advised by Professor Tom Anderson and Professor Arvind Krishnamurthy. My research has received NSF CAREER Award (2023), USENIX Security Distinguished Paper Award (2023), USENIX FAST Best Paper Award (2021), Amazon Research Award (2021), Google Academic Research Award (2024), IBM Academic Award (2021), and Meta Research Award (2022, 2021).

[Curriculum Vitae]

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Research

My research interests are (1) datacenter and cloud computing and (2) machine learning systems. Some research hightlights:

• Phoenix, a system service that exposes common application-level abstractions for speed and manageability. Its components include:
  • MCCS (SIGCOMM24), an collective communication system that decouples algorithm choice from applications, allowing the system to adjust algorithm choice without application interruption.
  • mRPC (NSDI23), an RPC architecture that supports efficient RPC-level policies and live upgradability.
• RDMABench, a test framework for RDMA software/hardware stack. Its components include:
  • Husky (NSDI23), a test suite for RDMA performance isolation for multi-tenancy. Our follow-up work, Harmonic (NSDI24), is the first step towards the performance isolation issues found by Husky.
  • Collie (NSDI22), a test suite for RDMA performance anomalies.
• A series of machine learning system research, including:
  • VTC (OSDI24), a large language model serving system with fairness guarantees.
  • Punica (MLSys24), a serving system for LoRA fine-tuned large language models.
  • JellyBean (VLDB23), a serving framework for ML workflows.
  • Alpa (OSDI22), a training framework for large neural network models.
  • TeraPipe (ICML21), a new parallelism dimension for training large language models.
  • Ansor (OSDI20), a compiler to generate efficient code for hardware accelerators.
• A series of exploration of using Rust in operating system development, including:
  • Enoki (EuroSys24), a operating system scheduler framework in Rust.
  • Bento (FAST21), a file system framework in Rust.

[All Publications]

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Students

I am very fortunate to work with a fantastic group of PhD students.

• Jingrong Chen
• Alexander Du (with Matthew Lentz)
• Yicheng Jin
• Xinhao Kong
• Jianxing Qin
• Yongji Wu (with Matthew Lentz)
• Yechen Xu

Past PhD Students:

• Samantha Miller (2023, with Tom Anderson). Databricks.

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Teaching

• Spring 2025: Systems for Machine Learning (CompSci 590)
• Spring 2024: Introduction to Computer Systems (CompSci 210)
• Spring 2023: Distributed Systems (CompSci 512)
• Fall 2022: Introduction to Operating Systems (CompSci 310)
• Spring 2022: Data Center Systems (CompSci 590.04)
• Fall 2021: Introduction to Operating Systems (CompSci 310)
• Fall 2020: Advanced Operating Systems (CompSci 510)

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Service

Organizer:

• 2022: Co-Chair for SIGCOMM Artifact Evaluation Committee

Technical Program Committee:

• 2025: NSDI, SIGCOMM, SIGMOD
• 2024: APNET, CoNEXT, NSDI, SIGMOD
• 2023: APNET, NSDI, SIGCOMM
• 2022: APNET, FAST, NSDI, SIGCOMM
• 2021: CoNEXT
• 2020: SIGCOMM

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Acknowledgement

I thank the following organizations and companies for their generous support: