Yun-Jhong Wu (吳允中)

PhD Candidate in Statistics
at the University of Michigan

About Me


My research interests focus on statistical and machine learning methods for massive network and matrix/tensor factorization models.

Link prediction

"people you may know", gene/protein-protein interactions, recommendation systems
Detecting missing relationships

Network data streams

E-mails, tweets, trending, correlation among stock prices, network traffic
Processing relational data in real-time

Side Projects

Portfolio theory

Neural networks


Work and Teaching Experience
  • Data Science Intern, Ford Motor Company, Dearborn, MI, USA, May-Dec. 2016
    - Deep learning for end-to-end parking space detection in videos
    - Spatio-temporal data analysis for air quality forecast
    - Route-based trip planning
  • Research Intern, Technicolor, Los Altos, CA, USA, May-Aug. 2015
    - Time series clustering for inferring user behavior from network traffic data
  • Graduate Student Instructor, the University of Michigan, Ann Arbor, MI, USA
    - Statistics for Financial Data (STATS 509), Winter 2017
    - Mathematical Statistics II (STATS 511), Winter 2016
    - Programming and Numerical Methods in Statistics (STATS 607A), Fall 2015
    - Optimization in Statistics (STATS 608A), Fall 2015
    - Introduction to Probability (STATS 425), Fall 2014
    - Introduction to Probability and Statistics (STATS 412), Fall 2012, Fall 2014
    - Introduction to Theoretical Statistics (STATS 426), Winter and Fall 2013, Winter 2014
  • Research Assistant, Institution of Statistical Science, Academia Sinica, Taiwan, Sep. 2011-Jun. 2012
  • Teaching Assistant,  Department of Mathematics, National Taiwan University, Taiwan
    - Advanced Statistical Inference (MATH 7604 and 7605), Fall 2010, Spring 2011
    - Calculus (MATH 1201 and 1202), Fall 2010, Spring 2011
    - Statistics (MATH 3601), Spring 2011
  • Research Assistant, Department of Sociology, National Taiwan University, Taiwan, Feb.-Jul. 2010

Publications and Presentations
  • Presentation: Learning network dynamics via regularized tensor decompositions. 2016 Joint Statistical Meetings. (Aug. 2016, Chicagoe, IL)
  • Presentation: Low-rank effects models for link prediction. 2015 Joint Statistical Meetings. (Aug. 2015, Seattle, WA)
  • Zhao, Y., Wu, Y.-J., Levina, E., and Zhu, J. (2017). Link prediction for partially observed networks. Journal of Computational and Graphical Statistics (in press).
  • Wu, Y.-J., and Chiang, C.-T. (2016). ROC representation for the discriminability of multi-classification markers. Pattern Recognition. (in press)
  • Wu, Y.-J., and Chiang, C.-T. (2013). Optimal receiver operating characteristic manifolds. Journal of Mathematical Psychology 57(5): 237-248.

Honors and Awards
  • Internship Award of Excellence, Ford Motor Company, Dearborn, MI, USA, July 2016
  • Special Mention for Teaching Award for Outstanding Graduate Student Instructor, Department of Statistics, the University of Michigan, Ann Arbor, MI, USA, May 2015
  • Chia-Lun Lo Fellowship, the University of Michigan, Ann Arbor, MI, USA, Dec. 2013
  • Gold Medal Award for Outstanding Master’s Thesis, Mathematical Society of the Republic of China, Taiwan, Dec. 2011
  • Professor Chen Wen-Chen’s Statistical Science Scholarship, Professor Chen Wen-Chen Memorial Foundation, Taiwan, Jul. 2011

  • TensorDecompositions.jl, a Julia implementation of tensor decomposition algorithms



Statistics, Machine Learning, Data Mining, Optimization

Computer Skills

Linux, Python, Java, C++, JavaScript, Julia, SQL, Hadoop, Spark


Running, Baking, Investing

Contact Me

Office: 436 West Hall, 1085 South University Ave, Ann Arbor, MI 48109
Skype: yunjhong_wu
WeChat: yunjhong

Yun-Jhong Wu and Yu-Pu Chen Yun-Jhong and Yu-Pu