Cho-Jui's Homepage

[ Basic Info ]

My name is Cho-Jui Hsieh. I am a 5th year Ph.D. student in University of Texas at Austin supervised by Prof. Inderjit Dhillon. I also work closely with Prof. Pradeep Ravikumar and Dr. Peder Olsen. I received my master degree in National Taiwan University under supervision of Prof. Chih-Jen Lin. My research interests are machine learning and optimization for big data and high dimensional problems. My research is supported by IBM Ph.D. fellowship in 2013-2015. Thanks, IBM!
[Curriculum Vitae] [Google Scholar Profile]


  • I will join Department of Computer Science and Department of Statistics at UC Davis as an Assistant Professor in Fall 2015.
  • The new Center for Big Data Analytics was formed in UT Austin. Please check the website.


  • University of Texas at Austin
    • Ph.D. student. Department of Computer Science, 2010 -- now.
  • National Taiwan University
    • M.S., Department of Computer Science & Information Engineering, 2007 -- 2009.
    • B.S., Department of Computer Science & Information Engineering, 2003 -- 2007.
    • B.S., Department of Mathematics, 2003 -- 2007.
  • IBM TJ Watson Research Center
    • Summer Intern, Jun 2013 -- Aug 2013.
    • Developed an efficient nuclear norm solver (published in ICML 2014).
    • Developed an autometic differentiation package for matrix functions.
  • LinkedIn
    • Summer Intern in SNA (Social Network Analysis) team, May 2012 -- Aug 2012.
    • Developed link prediction & clustering models based on organizational overlap (published in WWW 2013).
  • Google Inc, Taipei, Taiwan
    • Collaborate with Beijing research team, May 2008 - Sep 2008.
    • Applied linear SVM solvers to the explicit form of polynomially mapped data (published in JMLR, 2010).

[ Publications ]

[ Software ]

  • LIBLINEAR: A Library for large-scale linear classification.
  • DCSVM: A large-scale kernel SVM solver.
  • QUIC: A package for sparse inverse covariance estimation.
  • LIBPMF: A parallel matrix factorization library.
  • NMF_CD: Fast coordinate descent methods for non-negative matrix factorization.
  • AMD: An Automatic matrix differentiation library.
  • [ Selected Awards ]

    • IBM PhD Fellowship 2013--2014, 2014--2015.
    • NIPS oral presentation (top 1.4% submissions), 2013.
    • Best Paper Award, ICDM 2012.
    • Best Research Paper Award, KDD 2010.
    • Best Master's Thesis Award, Institute of Information and Computing Machinery, 2009.
    • Third Prize in the slow track of KDDCUP 2009.
    • Winner of SVM Track of Pascal Large Scale Learning Challenge in ICML 2008 Workshop.
    • International Olympiad in Informatics, Taiwan Representation (top 4 of Taiwan)
    • Second Prize of National College Programming Contest, Taiwan (with Kai-Wei Chang and Peng-Jen Chen)
    • Sixth Place in ACM ICPC Asia Regional programming, 2003 and 2006 (with Kai-Wei Chang and Peng-Jen Chen)