Research

Sensors measuring real-life physical processes are ubiquitous in today’s interconnected world. These sensors inherently bear noise that often adversely affects performance and reliability of the systems they support. Classic filtering-based approaches introduce strong assumptions on the time or frequency characteristics of sensory measurements, while learning-based denoising approaches typically rely on using ground truth clean data to train a denoising model, which is often challenging or prohi ...

The recent advancement in Cyber Physical Systems (CPS) and the Artificial Intelligence of Things (AIOT) has brought significant productivity and utility enhancement across all walks of life. However, safety and security concerns and usability challenges have prohibited the wide adoption of AI-powered smart "things" in large-scale real-world systems. My research aims to close this gap by enabling secure and safe interaction with Cyber-Physical Systems in a user-friendly manner. Smart commercial b ...

In this project, we analyzed the performance of the gVisor memory management subsystem, starting from benchmarking malloc and ending up focusing on MMAP. We further profiled MMAP performance within gVisor and identified its bottlenecks. We proposed an optimization in the free page searching algorithm of virtual memory space within gVisor (from O(N) to O(logN)). This optimization patch has been merged into production.

There is a presumption in human-computer interaction that laying out menus and most other material in neat rows and columns helps users get work done. The rule has been so implicit in the field of design to allow for no debate. However, the idea that perfect collinearity creates an advantage for both either search and or recall has rarely been tested. We conducted several experiments to test this. Note, I'm no longer on this project after Sep. 2018. The submitted paper is the latest version cont ...