I am currently a Machine learning engineering at Facebook, building newsfeed ranking models.
Prior to that, I worked as a Machine learning Engineering at Uber building several machine learning models and backend services, for example ETA prediction, map matching, payment risk fraud detection, smart ticket triaging system as well as end-to-end distributed feature selection tools.
Before I moved to the Bay area, I was a researcher in Abbott Laboratories, designing and implementing backend classification Alg. for AI computer vision based hematology diagnostic device.
I got my Ph.D. major in CS and focusing on machine learning from UT Arlington in 2013. My Ph.D. advisor is Dr. Heng Huang and I also worked closely with Dr. Chris Ding.
I have filed several U.S. patents and my paper has been cited more than 4000 according to Google scholar, https://scholar.google.com/citations?user=YtDC7VUAAAAJ&hl=en
Keywords: Image feature extraction, SIFT, HOG, GIST, CENTRIST, Color moment, Local binary pattern (LBP), motion segmentation,
regression, large scale feature learning, clustering, semi-supervised learning, sparse learning, logistic regression, SVM, SVR, multi-modal(multi-view) learning, transfer learning, recommendation system, collaborative filtering, information retrieval, convex optimization，deep learning (CNN, RNN and etc)
Software development :
version control: Git, SVN, TFS
OS: Windows, Linux, OSX
IDE: MS visual studio, Eclipse, IntelliJ, PyCharm
Product Language: C/C++, Java, Scala, Python
Scripts Language: Shell, Matlab
Big data: Apache Hive, Apache Spark, Apache Hadoop
Streaming: Apache Kafka
I am interested in staff position for research scientist, data scientist or data software engineering jobs related to big data, data mining, machine learning, information retrieval, computer vision and statistical learning.