Rui Meng
Ph.D. Student
Email:
rum20@pitt.edu
Website:
http://memray.me
Location:
Pittsburgh, PA, 15213
Research Interests
Natural Language Processing, Artificial Intelligence, Machine Learning
Publications
-
Deep Keyphrase Generation. [PDF][Slides][Code]
Rui Meng, Sanqiang Zhao, Shuguang Han, Daqing He, Peter Brusilovsky and Yu Chi.
55th Annual Meeting of Association for Computational Linguistics. (ACL 2017). -
Knowledge-based Content Linking for Online Textbooks. [PDF]
Rui Meng, Shuguang Han, Yun Huang, Daqing He and Peter Brusilovsky.
2016 IEEE/WIC/ACM International Conference on Web Intelligence. (WI 2016). -
Learning Semantic Representation from Restaurant Reviews: A Study of Yelp Dataset. [PDF]
Sanqiang Zhao, Shuguang Han, Rui Meng, Daqing He, Danchen Zhang.
iConference 2017. -
Automatic Classification of Citation Function by New Linguistic Features. [PDF]
Rui Meng, Wei Lu, Yu Chi and Shuguang Han.
iConference 2017. -
The Application of Query Performance Prediction to Result Merging of Aggregated Search
Rui Meng, Yong Huang, Wei Lu, Qi Wang
COINFO'13.
Education
University of Pittsburgh
Information Science and Technology - PhD student
Pittsburgh, PA, USA
Sep 2015
- Present
Wuhan University
Management Science and Engineering - Master
Wuhan, Hubei, China
Sep 2012
- Jul 2015
Wuhan University
Information Management and System - Bachelor
Wuhan, Hubei, China
Sep 2008
- Jul 2012
Experience
Google AI
Research Intern
May 2018
- Aug 2018
- Use Deep Learning techniques to recognize the hidden action patterns in mobile search
- Predict user satisfaction and quality of search results
Yahoo Research
Research Intern
May 2017
- Aug 2017
- Developed a novel evaluation method for dialogue systems
- Applied various kinds of NLP techniques and Big Data tools
Project Experience
Deep Keyphrase Generation
We apply a deep generative model (encoder-decoder model) on the task of keyphrase summarization, which provides a novel perspective on this long-studied problem. A copy mechanism is effectively employed to enhance the model with extractive ability. Experiments demonstrate our model not only outperforms baselines on keyphrase extraction benchmarks but also has the capability of predicting semantically related phrases.
Kaggle: Springleaf Market Response
A large-scale classification task aims to locate the target users for advertising. More than 290,000 customer records with nearly 2,000 anonymized features are used in this study. A complete pipeline has been implemented in this study, including data analysis (statistics and visualization), feature engineering (selection, reduction) and classification (ensemble models).
Citation Semantic Classification
Citation performs in different semantic roles in scientific papers. A fine-grined classification is conducted, based on support vector machine with multiple types of semantic features (n-grams, pos-tagging, linguistic pattern, typed dependency, entity etc.).
National Olympiad in Informatics in Provinces
The most influential programming competition for senior high school students in China. Similar to ACM Programming Contest, the NOIP require the contestants to show great IT skills as problem analysis, design of algorithms and data structures, programming and testing. The winners (less 1% of contestants) are recommended and accepted to top universities in China.
Technical Skills
Machine Learning:
TensorFlow, PyTorch, Theano, Scikit-learn, NLTK, Weka, Mallet, Stanford NLP toolkits
Research Tools:
MATLAB, LaTeX
Programming:
Python, Java, Linux, Bash, R, Web Development
Selected Awards, Scholarships, & Achievements
First Prize of National Olympiad in Informatics in Provinces
Awarded to top 1% participants in China for outstanding skills in algorithms and computer programming
China Computer Federation
Jan 2008
The First-Class Scholarship
Awarded to Top 5% students based on comprehensive ability evaluation
Wuhan University
Oct 2013
The Pacemaker to Graduate Student
Awarded to top students (1%) with extraordinary leadership
Wuhan University
Feb 2014
Interests
Technology: AI, AI, and AI, start-up
Fun: film, travelling