Last updated on Oct.8 2025, in air

About

Hi there! I am a second-year Ph.D. student in Computer Science at NYU Courant, advised by Prof. Aurojit Panda. Before that, I worked as a full-time Machine Learning Platform R&D Engineer in the Applied Machine Learning(AML) department at ByteDance, where I touched Kubernetes/Prometheus ecosystem, industrial cloud infrastructure and large-scale model training. I obtained my BSc in Computer Science at New York University Shanghai, and was advised by Prof. Grace Liu.

Currently my works cover computational frameworks on disaggregated memory pools, and efficient policy compliance of database-backed systems. I’ve also done research internship at Microsoft AHSI on high-performance network packet capturing.

Longer time ago, I have been working on fault tolerance for microservice systems and trustworthy network outsourcing for a while with Prof. Grace Liu. These experiences gift me the chance to (seriously) play with Ray, Datafusion, Envoy/Istio, GNS3 Emulator, etc.

I envision my research interest as:

• building easy-to-use and extensible cross-layer optimization techniques and interfaces (e.g. systems with resource disaggregation; scale-up/out-aware workload management) for next-generation cloud systems,

• building efficient and realible cloud clusters through efficient fault tolerance (Analogy: fast backup, sync recovery for programs; better congestion control and multi-path switching for networks).

• improving the observability of cloud systems and networks (e.g. shared logging and event infrastructure, hybrid timeseries databases) and assisting their reliability.

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

Contact me through the email address in the menu.