I am currently a Ph.D. candidate in computer engineering at the University of Maryland Baltimore County (UMBC), Baltimore, MD, USA, under advisement of Prof. Ryan Robucci and Prof. Nilanjan Banerjee. I joined UMBC ECLIPSE research cluster in 2013 and worked as teaching assistant and research assistant. Prior to this, I worked in China Mobile, Shenzhen, China for wireless network optimization from 2011 to 2013. I received my B.S. degree (2011) in electrical engineering from Beihang University, Beijing, China.

Research Interests

I am interested in building end-to-end realtime embedded system and exploring the optimization/acceleration design space cross different layers (sensors, hardware processing architecture, and signal processing). In specific, my works span on applications about RF-based cyber physical systems, computer vision-based assistive technology, and EEG-based realtime brain network visualization.

Projects

Micro Radar-based Non-contact Tongue Gesture Recognition

The project is targeted to recognize fine-grained movement/gestures wirelessly using micro radar sensors. We built a preliminery system, Tonuge-n-cheek, which can detect subtle facial gestures for people with severe paralysis to control their daily environment. A novel radar signal processing algorithm and a low latency micro-controller implementation is introduced in the system.

Paper Demo

RF-based Wearable Respiration Monitoring

We try to record human's respiration pattern to analyze the relation between asthma and environmental changes. We developed a non-intrusive system that uses a wearable micro radar to monitor human's breathing rate continuously.

Poster Demo

Vision-based Realtime Accessibility Issues Detection

The project aims at using machine vision to detect accessibility issues on sidewalks for helping people with visually-impairment. A prior-based framework is designed to accelerate the computer vision detection process in embedded devices, which uses a cooperation of human and machine.

Demo

Vision-based Accurate Bus Stop Localization

We target to detect and localize bus stop accurately to improve the accessibility of bus station for blind riders. A bus stop detection system is developed and implemented completely in a smartphone platform.

Poster Demo

Publications