Qu Tang, S.M., is a sixth year Ph.D. student in the Department of Electrical and Computer Engineering at Northeastern University, Boston, USA. His research focuses on the development of mobile health systems that integrate ideas from ubiquitous computing, machine learning, exercise science, and algorithms. Areas of special interest include algorithms for automated recognition of human behaviors using wearable sensors, and mobile technologies for measuring longitudinal human behaviors via biomarkers (e.g., motion, heart rate, etc).

Mr. Tang received his S.M. from Northeastern University in 2013 working on developing activity recognition algorithms at mHealth Research Group, and a B.S.E. degree in Electrical Engineering from the University of Electronic Science and Technology of China (UESTC) in 2010. He has published research on activity recognition, physical behavior measurement using accelerometers, and real-time system for measuring human behaviors. Mr. Tang has been serving as a reviewer for conferences and journals including IMWUT, Sensors, and JMIR.

Some research projects

💹 MIMS-unit algorithm

An open source and device-agnostic summarization algorithm for wearable accelerometer data
R Travis-CI build status codecov CRAN Status GitHub issues

🚬 Smoking detection

Hierarchical recognition model for puffing and smoking detection with wrist accelerometers
Python Bitbucket issues

🚶 Posture and activity detection

Best comibinations of body locations to detect posture and physical activities with wearable accelerometers
Python GitHub release GitHub issues

😄 Stereotypical movement detection

Intensively validated recognition model for stereotypical motion detection in Autism kids
R Matlab

📔 mHealth specification

Documentation of a human readable, compact data storage specification for mobile health data

Software projects

📈 Accelerometer and annotation visualizer

Synchronized, zoomable visualizer for multiple data streams, annotations
Javascript React GitHub issues

Arus

Python package to efficiently process and stream accelerometer data, and to build activity recognition models. PyPI version Build Status codecov GitHub issues

Real-time activity recognition app

A web app (with a REST API server backed by Python) to connect multiple Bluetooth wearable sensors, display real-time activity recognition predictions, and annotate human behaviors

Fun projects to satisfy my ego

🗒 Hexo theme cutie

A blog theme designed for Hexo static website generator engine
Javascript GitHub release GitHub issues Maintenance

🎮 Tower airdrop

A 2D motion-sensitive exercise game on Android
Android Maintenance

🎓 An opinionated curated list of resources for Ph.D. students

👤 About me

🇨🇳 From China
🇺🇸 Studying in US
⌨️ A daily coder
👨‍🎓 And a researcher
🎰 In machine learning
📱 And apps
🎮 Love games
👺 And anime
⚽️ And sports
🎵 And Chinese rap
🎥 And movies