Yining Wang

my photo

PhD student

Machine Learning Department,
School of Computer Science,
Carnegie Mellon University
Pittsburgh, PA, USA

Email: yiningwa at cs dot cmu dot edu
or ynwang dot yining at gmail dot com

Office: GHC 8021

I am a third year PhD student in the Machine Learning Department at Carnegie Mellon University. My advisor is Aarti Singh. Before coming to CMU, I was an undergraduate student at the Yao Class in Tsinghua University.

I am generally interested in statistical machine learning. Some topics that interest me include matrix completion and approximation, column subset selection and subspace clustering. I also want to know whether these tasks can be solved when only partial observations are available, and how can we improve over existing approaches by adaptively sampling/sensing in a feedback-driven manner.

Previously I have worked on Bayesian nonparametric modeling and the method of moments (spectral methods). I'm still interested in these topics. If you have common interests, feel free to stop by my office and we can have a chat.

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Carnegie Mellon University

PhD student in Machine Learning, School of Computer Science
Advisor: Aarti Singh

2014 - present

Tsinghua University

B. Eng. in Computer Science
Undergraduate thesis: Spectral Methods in Supervised Topic Modeling
Thesis advisor: Jun Zhu

2010 - 2014


Microsoft Research Redmond

Research Intern.
Supervisor: Dengyong (Denny) Zhou and Chong Wang.

June 2016 - Aug 2016

Research topics include deep neural network and natural language processing systems.

Symantec Research Labs

Research Intern.
Supervisor: Petros Efstathopoulos and Kevin Roundy.

June 2015 - Aug 2015

Design and implementation of Project Harbinger, a system for enterprise level malicious attack prediction based on collaborative filtering.

Tsinghua University

RA at State Key Laboratory of Intelligent Technology and Systems.
Advisor: Jun Zhu

Aug 2013 - Jul 2014

Research topics include small-variance asymptotic analysis for Bayesian nonparametric models and spectral learning for latent variable models.

Massachusetts Institute of Technology

Undergraduate exchange program at Department of EECS

Jan 2013 - May 2013

Courses: Inference and Information, Nonlinear Programming and Automatic Speech Recognition
Research advisors: Jingjing Liu and Cynthia Rudin
Research topics: semantic role labeling in spoken dialogue systems and discrete optimization for learning to rank applications.

Microsoft Research Asia

Research intern at Technical Strategies group
Supervisors: Eric Chang and Junichi Tsujii

Oct 2011 - Jan 2013

Development of natural language processing applications in the medical informatics domain.