Peng Qi
Peng Qi
Research, Learn, Code, and Play.

Brief Bio

I am currently a Ph.D. student at the Computer Science Departmentof Stanford University.

My research interests broadly cover topics in machine learning, especially deep learning, with which I seek to solve real-world problems more effectively in applications including natural languages, speech recognition, and computer vision. I also dabble in GPGPU programming, computer graphics, data mining and data visualization.

[CV (slightly outdated)]    [Publications]


Education & Professional Experience

2015.9 - PresentPh.D. Student & Research Assistant, Computer Science Department, Stanford University
2013.9 - 2015.6Master of Science & Research Assistant, Computer Science Department, Stanford University
2012.7 - 2013.6Research Assistant, State Key Laboratory of Intelligent Technology & Systems, Department of Computer Science and Technology, Tsinghua University
2008.8 - 2012.7Bachelor of Engineering, School of Software, Tsinghua University (Excellent Graduate)


  • Andrew L. Maas, Peng Qi, Ziang Xie, Awni Y. Hannun, Christopher T. Lengerich, Daniel Jurafsky, Andrew Y. Ng. Building DNN Acoustic Models for Large Vocabulary Speech Recognition. In arXiv, 2015. [HTML]    [BibTeX]
  • Andrew L. Maas, Awni Y. Hannun, Christopher T. Lengerich, Peng Qi, Daniel Jurafsky, Andrew Y. Ng. Increasing Deep Neural Network Acoustic Model Size for Large Vocabulary Continuous Speech Recognition. In arXiv, 2014. [Replaced by an extended version]
  • Xiaolin Hu, Jianwei Zhang, Peng Qi, and Bo Zhang. Modeling Response Properties of V2 Neurons with a Modified K-Means. In Neurocomputing, 2014.[PDF]   [HTML]    [BibTeX]
  • Peng Qi and Xiaolin Hu. Learning Nonlinear Regularities in Natural Images by Modeling the Outer Product of Image Intensities. Neural Computation, 2013. [PDF]   [Code]   [HTML]    [BibTeX]
  • Peng Qi, Shuochen Su, and Xiaolin Hu. Modeling Outer Product of Features for Image Classification. ICACI 2013. [PDF]    [BibTeX]
  • Xiaolin Hu, Peng Qi, and Bo Zhang. Hierarchical K-Means Algorithm for Modeling Visual Area V2 Neurons. In Neural Information Processing, Lecture Notes in Computer Science, pp. 373–381, Springer Berlin / Heidelberg, 2012. 10.1007/978-3-642-34487-9_46. Best Paper Award
    [PDF]   [HTML]    [BibTeX]

Honors and Awards

  1. 2012 Outstanding Graduate of Tsinghua University
  2. 2011 National Scholarship (top 3% students)
  3. 2010 Citibank Scholarship (for overall excellence)
  4. 2009 Ge-Ru Zheng's Scholarship (for study excellence)
  5. 2008-2011 Freshman Scholarship (Ranked 3rd of Guizhou Province in National College Entrance Exam)


  1. CS 224s Spoken Language Processing, Spring 2014 (Check out Homework 3 I designed)
  2. CS 145 Introduction to Databases, Summer 2014 (Better Homeworks I created, and midterm, final review slides I made)

Work Experience and Social Service

  1. 2013-2014 Backend Engineer & Machine Learning consultant (Part-Time),, Beijing
  2. 2010-2011 Vice President of Students' Union, School of Software, Tsinghua University

Last Updated: Jan. 21, 2015