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qutang/README.md

截屏2021-12-18 下午11 09 27

🎉 - Hello! My name is Qu Tang. I'm currently working as a Senior Research Scientist at Zepp Health, base in Shanghai, China.

🏫 - I received my Doctoral degree in Philosophy, majored in Computer Engineering in August, 2021 and graduated from the Department of Electrical and Computer Engineering at Northeastern University, Boston, USA. I worked as a research assistant at mHealth Research Group @ NU with Prof. Stephen Intille. I previously received my M.S. degree from Northeastern University in 2014 and my B.S. degree in Electrical Engineering from University of Electronic Science and Technology of China (Chengdu, China) in 2010. I also serve as a reviewer for several academic conferences and journals (including ACM IMWUT, IEEE Sensors, AAAI, and JMIR).

💡 - My research interests include the development of mobile health sensing and intervention systems, algorithms for automatic recognition of human behavior using wearable sensors, and the measurement of human behavior patterns over long time spans through biomarkers (e.g., exercise, heart rate, etc.). The field involves the intersection of machine learning, computer science, signal processing, human-computer interaction, motion science, and behavioral science.

☎️ - I'm open for academic or industrial collaboration, co-authoring books or other publications, consulting or entrepreneual opportunities, please contact me via Email or LinkedIn, my publications are listed on the Google Scholar profile.


🎉 - 大家好,我叫唐曲, 现在在华米科技担任算法高级研究员。

🏫 - 我于2021年8月毕业于美国波士顿大学东北大学电气与计算机工程系,师从Stephen Intille教授,同时获得计算机工程专业的哲学博士学位。我于2014年从东北大学获得硕士学位,于2010年获得中国电子科技大学(成都)的电机工程学学士学位。我也同时为一些学术会议和期刊(包括IMWUT,Sensors和JMIR)担任审稿人。

💡 - 我感兴趣的研究主要包括移动健康检测和干预系统的开发,使用可穿戴式传感器自动识别人类行为的算法,以及通过生物标记(例如运动,心率等)测量长时间跨度范围内人类行为模式。该领域涉及机器学习,计算机科学,信号处理,人机交互,运动科学以及行为科学的交叉应用。

☎️ 我对学术或工业界的合作机会,共同创作,独立咨询或创业机会持开放态度,如果有任何合作意向,请通过电子邮件联络我,我的Google学者主页展示了我所有的出版论文。

Pinned

  1. mHealthGroup/MIMSunit mHealthGroup/MIMSunit Public

    MIMS-unit is abbreviated for Monitor Independent Movement Summary unit. This measurement is developed to harmonize the processing of accelerometer data from different devices. Associated R package …

    PostScript 10 4

  2. tang_msse_2020 tang_msse_2020 Public

    Source codes and dataset for "Multi-site sensing for activity recognition using accelerometers" published in Medicine and Science in Sports and Exercise 2020

    Python 2

  3. stereotypy_ubicomp_14 stereotypy_ubicomp_14 Public

    Source codes for "Moving towards a real-time system for automatically recognizing stereotypical motor movements in individuals on the autism spectrum using wireless accelerometry." published in Ubi…

    MATLAB

  4. tang_pervhealth_14 tang_pervhealth_14 Public

    Dataset and source codes for "Automated Detection of Puffing and Smoking with Wrist Accelerometers" published at Pervasive Health 14'

    Python 1