Yuwei Xiao 肖煜玮

I am a first-year CS PhD student at UCLA advised by Prof. Eunice Jun.

My research interests lie in the intersection of human-computer interaction, information visualization, and end-user programming. Specifically, I design interactive systems that help individuals (especially non-expert) understand complex information, uncover subtle insights, and make informed decisions.

Currently, I am developing an interactive elicitation approach to support experts in effectively and accurately expressing their domain knowledge in statistical analysis.

Previously, I was fortunated to work with Prof. Haojian Jin at UCSD. I earned my bachelor degree from Southern University of Science and Technology.

news

Sep 26, 2024	Started my PhD journey at UCLA CS!
May 11, 2024	Served as a Student Volunteer at CHI 2024!
Oct 29, 2023	Attended UIST 2023 in San Francisco!

selected publications

IoTProsector

On the Feasibility of Reasoning about the Internal States of Blackbox IoT Devices Using Side-Channel Information

Wei Sun^*, Yuwei Xiao^*, Haojian Jin, and 1 more author

2023

Abs DOI

Internet of Things (IoT) devices are typically designed to function in a secure, closed environment, making it difficult for users to comprehend devices’ behaviors. This paper shows that a user can leverage side-channel information to reason fine-grained internal states of black box IoT devices. The key enablers for our design are a multi-model sensing technique that fuses power consumption, network traffic, and radio emanations and an annotation interface that helps users form mental models of a black box IoT system. We built a prototype of our design and evaluated the prototype with open-source IoT devices and black-box commercial devices. Our experiments show a false positive rate of 1.44% for open-source IoT devices’ state probing, and our participants take an average of 19.8 minutes to reason the internal states of black-box IoT devices.