research
My research centers on trustworthy, efficient computation. I am interested in security, privacy, verifiable trust, and performance, with the goal of ensuring that execution remains protected in shared environments and that results are reliable without sacrificing efficiency.
I have had the opportunity to explore these questions through the following research areas.
Confidential Computing
I work on enabling users to run workloads on third-party cloud infrastructure with provable confidentiality and integrity guarantees while preserving the performance that makes cloud computing viable. This involves leveraging hardware-assisted Trusted Execution Environments (TEEs) to secure data in use.
Securing 5G network functions on third-party cloud infrastructure using Trusted Execution Environments (TEEs), with confidentiality and integrity guarantees that preserve practical performance.My initial work explored running cellular network workloads in TEE environments, and I am interested in extending this direction to broader modern computing infrastructure, including cloud-native services, distributed systems, and HPC workloads.
Empirical Systems Research
I investigate performance variability in systems experiments. My goal is to help researchers trust that their measurements are representative and reproducible, rather than artifacts of environmental interference.
Characterizing how performance results shift across environmental conditions, including how much conclusions change, whether individual runs can be treated as independent samples, and which conditions drive the largest differences. This work grew out of performance variability I observed while working with Trusted Execution Environments, and aims to improve the generalizability and reproducibility of systems experiments across heterogeneous hardware.