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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**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。

Qu Tang's Projects

.github icon .github

The default health files for qutang's projects

arus-components-hci icon arus-components-hci

arus plugins that include streams, pipelines and broadcasters that may include human computer interactions through GUI, voice or other interfaces.

bpl icon bpl

Bayesian Program Learning model for one-shot learning

dockers icon dockers

Dockers used in my research projects

imagecaptioning.pytorch icon imagecaptioning.pytorch

image captioning codebase in pytorch(finetunable cnn in branch "with_finetune";diverse beam search can be found in 'dbs' branch; self-critical training is under my self-critical.pytorch repository.)

kalman-and-bayesian-filters-in-python icon kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

libol icon libol

Library for Online Learning algorithms

mhealth-gt3x-converter-public icon mhealth-gt3x-converter-public

A standalone app written in Java to convert raw Accelerometer data from GT3X File Format into mHealth format. Supports both the NHANES-GT3X format (V1) and the newest GT3X-File format (V2).

mhealthr icon mhealthr

R package to support data io, manipulation and visualization for mhealth specification

mixture-of-experts icon mixture-of-experts

A Pytorch implementation of Sparsely-Gated Mixture of Experts, for massively increasing the parameter count of language models

omniglot icon omniglot

Omniglot data set for one-shot learning

padar icon padar

commandline data processing and machine learning tool for mhealth datasets. Discarded. See https://github.com/qutang/arus

padar_converter icon padar_converter

Converters for third-party sensors to mhealth format for padar package

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