• Catherine Qi Zhao

    Assistant Professor
    Department of Computer Science and Engineering
    University of Minnesota

    Office: Keller 6-189
    Phone: (612) 301-2115
    Email: qzhao at cs.umn.edu

  • My research is in the areas of computer vision, machine learning, computational neuroscience, and healthcare. In particular, I am interested in providing theoretical foundations and computational innovations in computer vision, inventing new machine learning methods inspired by many AI problems including vision, brain sciences, and medical sciences, and building intelligent systems that leverage both artificial and human intelligence.

    My recent focus includes understanding neural networks and developing networks and other AI techniques for emerging applications in healthcare and brain science, for example, to understand and identify neurodevelopmental disorders with visual behaviors, and to decode human motor intention with amputee patients based on peripheral nerve neural recordings.


  • our work on shallowing deep neural networks is out. [pdf]
  • I will be an AC for WACV 2019, CVPR 2019, and IJCAI 2019.
  • our work on emotion and attention is out. [project page]
  • we received an NSF SHF grant (With Chris Kim and Sachin Sapatnekar) to develop time-based deep neural networks.
  • we are organizing the 3rd LSUN Saliency Challenge, in conjuection with CVPR 2017.
  • the new book I edited is out! -- it provides an overview of vision from various perspectives, ranging from neuroscience to cognition, and from computational principles to engineering.

  • our work on autism photo is out in Current Biology.
  • I joined the University of Minnesota Twin Cities as an assistant professor.
  • commentary about our autism work appears in Neuron!
  • press release at Business Insider, Huffington Post, MedicalXpress, Daily Mail, Futurity, NUS, and Caltech
  • our work is on the cover of Neuron! [pdf]


  • Database

    • SALICON database. Saliency in Context - a large-scale attention database on MS COCO images. Jiang et al. CVPR [pdf] [bib]
    • EMOd database. EMOtional attention dataset- a database with rich sentiment and semantic attributes (4302 objects, 33 high-level attributes). Fan et al. CVPR [pdf] [bib]
    • OSIE database. Object and Semantic Images and Eye-tracking database - a database for object and semantic saliency (700 images, 5551 objects with fine contour and semantic attribute labeling). Xu et al. JoV [pdf] [bib]
    • EyeCrowd database. Eye Fixations in Crowd database - a database for saliency in crowd. Jiang et al. ECCV [pdf] [bib]


  • Code