Chen-Chen Yu 于晨晨

Pattern Recognition Researcher

AI Lab, Lenovo Research, Beijing, China.

Bio

I am Chenchen Yu. Now I work at Lenovo Research as a pattern recognition researcher in Beijing, China. I got my bachelor and master degree from Beijing University of Posts and Telecommunications in 2015 and 2018 respectively. I once worked in Didi Chuxing(the leading one-stop mobile transportation platform in China) and Baidu Tech(the biggest search company in China) as a student intern.

My research direction is machine learning, deep learning, speech enhancement, acoustic sound event detection, etc.

My Github: https://github.com/yucc2018/

My Blog: http://yucc.me/blog/

News & Activities

Education

Mar. 2018 - Aug. 2015    M.S. in Information and Communication Engineering    Beijing University of Posts and Telecommunications

Aug. 2011 - Jul. 2015    B.S. in Information Engineering    Beijing University of Posts and Telecommunications

Research Experience

Artificial Intelligence Lab, Lenovo Research, Beijing, China    Full-time Pattern Recognition Researcher    Apr. 2018 - present

Machine learning(SVM/GBDT, etc) and deep learning (DNN/CNN/LSTM, etc) based environmental sound classification and analysis.

Recommended System Platform, Baidu co., ltd, Beijing,China    Algorithm Engineer Intern    Dec. 2017 - Mar. 2018

Time and location based Baidu feed recommendation. When you go to work, to the tourist attractions, or friday, or weekend, we will recommend the appropriate information to you by algorithms.

Artificial Intelligence Lab, Didi Chuxing co., ltd, Beijing, China    Algorithm Engineer Intern    Jul. 2017 - Nov. 2017

Using spark processing driver characteristic data, according to part of the label data, using xgboost and other model methods to predict the satisfaction of the full Didi Chuxing platform drivers.

Pattern Recognition and Intelligent System Lab, BUPT, Beijing, China    Graduate student    Aug. 2015 – Mar. 2018

Working on abnormal audio event classification, I extracted time domain and frequency features and extract the statistical features of an audio. Experiments were performed using different classifiers such as Support Vector Machine, Random Forest and Deep Neural Network in the public data sets including UrbanSound8K and ESC-10.

Pattern Recognition and Intelligent System Lab, BUPT, Beijing, China    Undergraduate student    Dec. 2014 – Jul. 2015

I did the project of my undergraduate thesis about automatic tagging of text.

Skills

Languages: C++, Python

Frameworks: NumPy, SciPy, Pandas, PyTorch, Keras

Systems: Linux, OSX, Windows


### Publications

##### Patent

##### Journal papers

##### Conference papers



### Awards

### Demos

 

 

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Last update: July 2018