About me

I am a PhD candidate in Computer Science at UC Santa Barbara. I study computer architecture with Prof. Tim Sherwood and I am interested in the design of private computer systems and applications. My interdisciplinary research spans computer architecture, privacy, computer vision, and machine learning.

In my PhD, I have explored the privacy of program traces where the intent is to minimize information leakage to ensure safer sharing of program behavior for co-optimization. The key trade-off is balancing information leakage while maintaining utility of the privatized traces. Trace wringing was published in ASPLOS 2019 and recognized in IEEE Micro’s Top Picks from Computer Architecture Conferences 2020. Previously, I have worked on PyRTL, a Python-based RTL specification language, and built the OpenTPU and cryptographic cores on it. I have also worked on Charm, a high-level architecture modeling language.

During my internship at Facebook Reality Labs Research, I worked on building privacy into AR/VR pipelines. With a novel reverse engineering attack, I demonstrated that feature descriptors, previously considered safe to share, can be used to reconstruct raw user images. I present mitigations that trade off privacy (quality of reconstruction) and utility (in terms of localization accuracy). At Microsoft Research, I developed an automated framework for resource- and architecture-aware graph partitioning and fine tuning quantized neural network layers on the Brainwave NPU.