Last updated on Jan. 5 2024

About

I am a full-time Machine Learning Platform R&D Engineer in the Applied Machine Learning(AML) department at ByteDance, Ltd. I obtained my BSc in Computer Science at New York University Shanghai.

I have been working as a research assistant at NYUSH since winter 2021, participating in two papers in secure network management and configuration sharing, for which I actively contribute in many aspects including system implementation, algorithm design, evaluations, etc. I have been working on fault tolerance on Service Mesh for QoS-aware applications at NYU since summer 2023.

I am looking for research opportunity in Distributed Systems and Networks, I am also willing to explore in PL/SE for Systems. Specifically, I am currently interested in:

• building efficient and realible cloud clusters through efficient fault tolerance and effective cluster management.

• building easy-to-use and extensible cross-layer acceleration techniques and interfaces (e.g. optimizing usage of eBPF, smartNIC; isolation of in-network resources in multi-tenant context), and

• improving the observability of cloud systems and networks (e.g. distributed tracing, XDP tracepoints).

That said, I am open to any interesting problems in the broader Systems area.

Contact me through the email address in the menu.