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Qixing Huang

Research Assistant Professor
Toyota Technological Institute at Chicago

6045 S. Kenwood Ave, Chicago, IL 60637

Phone: (773)834-9873

Email: huangqx at ttic dot edu



Short Bio

Qixing Huang obtained his PhD in Computer Science from Stanford University in 2012. From 2012 to 2014 he was a postdoctoral research scholar at Stanford University. He received his MS and BS in Computer Science from Tsinghua University. He has also interned at Google Street View, Google Research and Adobe Research. His research spans computer vision, computer graphics, computational biology and machine learning. In particular, his recent focus is on developing machine learning algorithms (particularly deep learning) that leverage Big Data to solve core problems in computer vision, computer graphics and computational biology. He is also interested in statistical data analysis, compressive sensing, low-rank matrix recovery, and large-scale optimization, which provide theoretical foundation for much of his research.

Curriculum Vitae


Google Scholar

  • I'll be starting as an Assistant Professor in the Computer Science department at UT Austin in fall 2016. I will be looking for motivated students, so please contact me if you are interested!


    Recent News

  • 7/2016: Our papers on "Unsupervised Texture Transfer from Images to Model Collections" and "A Scalable Active Framework for Region Annotation in 3D Shape Collections" are conditionally accepted by SIGGRAPH ASIA' 2016.
  • 7/2016: Our paper on "Capturing Dynamic Textured Surfaces of Moving Targets" is accepted by ECCV' 2016.
  • 5/2016: Our paper on "City-Scale Map Creation and Updating using GPS Collections" is accepted by KDD' 2016.
  • 4/2016: Our paper on "Connected Fermat Spirals for Layered Fabrication" is accepted by SIGGRAPH' 2016.
  • 3/2016: Our RECOMB 2016 paper "Joint alignment of multiple protein-protein interaction networks via convex optimization" is accepted by Journal of Computational Biology.
  • 3/2016: Two ORAL papers accepted at CVPR 2016. Both of them are on dense correspondences using CNN. One tackles the problem of correspondence representation, and another tackles the problem of training data.
  • 3/2016: Upcoming visits: Purdue University, University of Texas, Austin, University of California Riverside, Washington University at St. Louis, University of Toronto, University of Southern California.
  • 12/2015: The source code of my SIGGRAPH'15 paper on single-view reconstruction via joint analysis of image and shape collections can be found here.
  • 12/2015: A paper titled "Joint alignment of multiple protein-protein interaction networks via convex optimization" has been accepted for presentation in RECOMB 2016. This is a joint work with Somaye Hashemifar and Jinbo Xu from TTI Chicago.
  • 11/2015: Submitted two proposals to NSF.
  • 11/2015: A joint proposal with Jason Salavon and William Catino (UChicago), and Sean Keller (IIT) on "Critical Computation: Machine Learning and Questions of Quality in Art and Design" has been granted by UChicago Neubauer Collegium Research Initiatives. Looking forward to collaborating with artists on doing some fun research.
  • 11/2015: Co-authored three submissions to CVPR 2016.
  • 10/2015: I gave two invited colloquium talks at UT Austin. The CS talk is on shape-driven image-based modeling, and the ICES talk is on data-driven map computation using constrained matrix optimization.
  • 08/2015: I gave an invited talk at Berkeley VCL seminar on shape-driven image-based modeling.

    Student Supervision

  • Hai Wang (TTIC), 10/2014-01/2015
  • Xi Chen (University of Maryland), 01/2015 -- 06/2015
  • Zimo Li (University of Chicago), 03/2015 --
  • Guilin Liu (George Mason University), 05/2015 -- 08/2015
  • Tuanfeng Wangyang (University of College London), 11/2015 -- 02/2016

  • Last update: Nov. 25, 2015