I am a graduate student at Carnegie Mellon University, Pittsburgh, PA. I'm in the Master of Computational Data Science program.
I got my Bachelor's degree from IEEE Honor Class at Shanghai Jiao Tong University, majoring in Computer Science & Technology. I leaded or participated in several successful research projects during the undergraduate years.
I am passionate and motivated. I love to design & make cool stuffs. SCROLL DOWN to see more!
I have years of experience in full-stack web development. I enjoy designing the UI/UX and the architecture of applications and implementing them!
Also I am enthusiastic about software systems design and engineering. I've completed several mobile systems & intelligent transportation systems (based on smart-phones) as research projects. I was a Software Engineer Intern at Microsoft, Shanghai.
ChiChi is the SJTU official food management committee. The ChiChi app is designed to present the daily feasts students can get from SJTU's dining halls. The app provides visually-tasty meal suggestions with beautiful photos from the shutterbugs at SJTU Photography Association. If you are hungry, just keep hitting the refresh button. You'll get HUNGRIER! :-)
GoToDye is a Go AI engine written in C.
This project was the runner-up in the Computer Go Competition of my sophomore course Artificial Intelligence. The algorithm was based on Monte Carlo Tree Search.
Aero is an indoor localization system based on visual SLAM conducted by AR.Drone and a smartphone taped to the drone.
AR.Drone 2.0 has embedded sensors, camera and WiFi. The visual SLAM algorithm collects data from the IMU on AR.Drone with camera video flow, and utilizes a smartphone to compute the indoor map and current location of the drone.
HuanKr is an online course sharing and exchanging platform.
With user's permission, HuanKr can import schedule from SJTU Electsys with one click. Huankr provides functions like note sharing, assignment notification, etc.
CityDrive is a driving speed optimizing system based on smartphone. It aimed at implementing a speed-optimizing driving system, so that the drivers who follow the suggestion speed provided by this system will pass every intersection in green light without pulling up. A paper based on this work was accepted by IEEE INFOCOM, 2014.
VDNet is a quadcopter assisted sparse VANET system. I proposed a novel VANET design in which some vehicles carries an on-board quadcopters. A vehicle location prediction algorithm was proposed to improve efficiency in this delay-tolerant network. A paper based on this work was submitted to IEEE INFOCOM, 2015.
This project aims at only using data collected from sensors on smartphones of the drivers to detect lanes on roads, and utilizes methods of crowdsourcing and machine learning. A paper based on this work was submitted to Mobisys, 2015.