Danyang Zhuo

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), FAST Best Paper Award (2021), Amazon Research Award (2021), IBM Academic Award (2021), and Meta Research Award (2022, 2021).

[Curriculum Vitae]

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:
- mRPC (NSDI23), an RPC architecture that supports efficient RPC-level policies and live upgradability.
HostBench, a test framework for RDMA software/hardware stack. Its components include:
- Husky (NSDI23), a test suite for RDMA performance isolation for multi-tenant RDMA.
- Collie (NSDI22), a test suite for RDMA performance anomalies.
A series of machine learning system research, including:
- 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/serving large language models.
- Ansor (OSDI20), a compiler to generate efficient code for hardware accelerators.

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

I have a great time working with other fantastic PhD students, including Zhuohan Li, Shihan Lin, Jack Snyder, Kaiyuan Zhang, Lianmin Zheng, Xiangfeng Zhu, Siyuan Zhuang.

Organizer:

Technical Program Committee:

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