She/Her
Associate Professor, Department of Computer Science & Engineering
Contact
6-189 Kenneth H. Keller Hall
200 Union Street Se
Minneapolis, MN 55455
She/Her
Associate Professor, Department of Computer Science & Engineering
Ph.D. in Computer Engineering, University of California, Santa Cruz (2009)
B.S. in Computer Science, Zhejiang University (2004)
Catherine Qi Zhao joined the Department of Computer Science & Engineering as an assistant professor in 2016 and was promoted to an associate professor in 2021. Zhao also serves as an IEEE member. Prior to her time at the University, she served as a postdoctoral researcher at California Institute of Technology from 2009-11 and as an assistant professor at the National University of Singapore from 2011-16. Zhao received a Chancellor’s Fellowship in 2004 and a Mei Wang Graduate Fellowship in 2005 from the University of California, Santa Cruz.
Zhao’s research is in the areas of artificial intelligence, computer vision, machine learning, and AI for humans. In particular, her gorup provides theoretical foundations in computer vision, invents application-specific machine learning methods, and develops trustworthy systems that leverage both artificial and human intelligence. Our recent focus includes understanding neural networks, and innovating explainable and generalizable AI methods. We also emphasize the role of humans in AI and develop AI to benefit humans, especially those in need.
Research Division
Robotics and Artificial Intelligence
Current Research
Google Scholar
Visual Information Processing Lab
Ph.D. Graduates
Yan Luo (2022); Sthitie Bom (2022); Qiang Zhou (2017, National University of Singapore); Ming Jiang (2017, National University of Singapore); Chengyao Shen (2016, National University of Singapore); Weiquan Lu (2014, National University of Singapore).
Selected Grants
RI: Small: Visual How: Task Understanding and Description in the Real World
Zhao, C.; National Science Foundation; 6/15/22 - 5/31/25
EAGER: Interpretable and Generalizable AI for Smart Manufacturing
Zhao, C.; National Science Foundation; 8/15/22 - 7/31/24
RI: Small: Exploring Rationale behind Visual Understanding: Combining Attention and Reasoning
Zhao, C.; National Science Foundation; 8/1/19 - 7/31/23
Fan, S., Shen, Z., Jiang, M., Koenig, B.L., Kankanhalli, M.S., Zhao, Q. (2023). Emotional Attention: From Eye Tracking to Computational Modeling. IEEE Transactions on Pattern Analysis and Machine Intelligence. PP (2), [1682-1699].
DOI: 10.1109/tpami.2022.3169234
Luo, Y., Wong, Y., Kankanhalli, M.S., Zhao, C. (2023). Learning to Minimize the Remainder in Supervised Learning. IEEE Transactions on Multimedia. [1738-1748].
DOI: 10.1109/TMM.2022.3158066
Chen, S., Jiang, M., Yang, J., Zhao, Q. (2022). Attention in Reasoning: Dataset, Analysis, and Modeling. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44 (11), [7310-7326].
DOI: 10.1109/TPAMI.2021.3114582
Bowyer, K., Medioni, G., Scheirer, W., Anand, S., Farrell, R., Souvenir, R., Zhao, C. (2022). Message from the General and Program Chairs. Proceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022. [xiv].
DOI: 10.1109/WACV51458.2022.00005
Nguyen, A.T., Drealan, M.W., Khue Luu, D., Jiang, M., Xu, J., Cheng, J., Zhao, Q., Keefer, E.W., Yang, Z. (2021). A portable, self-contained neuroprosthetic hand with deep learning-based finger control. Journal of neural engineering. 18 (5), [056051].
DOI: 10.1088/1741-2552/ac2a8d
Luu, D.K., Nguyen, A.T., Jiang, M., Xu, J., Drealan, M.W., Cheng, J., Keefer, E.W., Zhao, Q., Yang, Z. (2021). Deep Learning-Based Approaches for Decoding Motor Intent From Peripheral Nerve Signals. Frontiers in Neuroscience. [667907].
DOI: 10.3389/fnins.2021.667907
Zhang, Y., Jiang, M., Zhao, Q. (2021). Explicit Knowledge Incorporation for Visual Reasoning. In Proceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021. (1356-1365). (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. (1063-6919)). IEEE Computer Society.
DOI: 10.1109/CVPR46437.2021.00141
Luo, Y., Wong, Y., Kankanhalli, M.S., Zhao, Q. (2021). Learning to Predict Trustworthiness with Steep Slope Loss. In Ranzato, M.A., Beygelzimer, A., Dauphin, Y., Liang, P.S., Wortman Vaughan, J. (eds). Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. (21533-21544). (Advances in Neural Information Processing Systems. 26. (1049-5258)). Neural information processing systems foundation.
Chen, X., Jiang, M., Zhao, Q. (2021). Leveraging Human Attention in Novel Object Captioning. In Zhou, Z.H. (ed). Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021. (622-628). (IJCAI International Joint Conference on Artificial Intelligence. (1045-0823)). International Joint Conferences on Artificial Intelligence.
Chen, X., Jiang, M., Zhao, Q. (2021). Predicting Human Scanpaths in Visual Question Answering. In Proceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021. (10871-10880). (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. (1063-6919)). IEEE Computer Society.
DOI: 10.1109/CVPR46437.2021.01073
Zhang, Y., Jiang, M., Zhao, Q. (2021). Saliency prediction with external knowledge. In Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021. (484-493). (Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021.). Institute of Electrical and Electronics Engineers Inc..
DOI: 10.1109/WACV48630.2021.00053
Chen, X., Jiang, M., Zhao, Q. (2021). Self-distillation for few-shot image captioning. In Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021. (545-555). (Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021.). Institute of Electrical and Electronics Engineers Inc..
DOI: 10.1109/WACV48630.2021.00059
Furon, T., Liu, J., Rawat, Y., Zhang, W., Zhao, Q. (2021). Trustworthy AI'21: 1st International Workshop on Trustworthy AI for Multimedia Computing. In MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia. (5708-5709). (MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia.). Association for Computing Machinery, Inc.
DOI: 10.1145/3474085.3478583
Nguyen, A.T., Xu, J., Jiang, M., Luu, D.K., Wu, T., Tam, W.K., Zhao, W., Drealan, M.W., Overstreet, C.K., Zhao, Q., Cheng, J., Keefer, E.W. (2020). A bioelectric neural interface towards intuitive prosthetic control for amputees. Journal of neural engineering. 17 (6), [066001].
DOI: 10.1088/1741-2552/abc3d3
Fan, S., Koenig, B.L., Zhao, Q., Kankanhalli, M.S. (2020). A Deeper Look at Human Visual Perception of Images. SN Computer Science. 1 (1), [58].
DOI: 10.1007/s42979-019-0061-5
Chen, S., Jiang, M., Yang, J., Zhao, Q. (2020). AiR: Attention with Reasoning Capability. In Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (eds). Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings. (91-107). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 12346 LNCS. (0302-9743)). Springer Science and Business Media Deutschland GmbH.
DOI: 10.1007/978-3-030-58452-8_6
Liang, H., Jiang, M., Liang, R., Zhao, Q. (2020). A structure-guided approach to the prediction of natural image saliency. Neurocomputing. [441-454].
DOI: 10.1016/j.neucom.2019.09.085
Jiang, M., Chen, S., Yang, J., Zhao, Q. (2020). Fantastic answers and where to find them: Immersive question-directed visual attention. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. [9157348]. [2977-2986].
DOI: 10.1109/CVPR42600.2020.00305
Li, J., Xu, Z., Wang, Y., Zhao, Q., Kankanhalli, M.S. (2020). GradMix: Multi-source transfer across domains and tasks. In Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020. (3008-3016). (Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020.). Institute of Electrical and Electronics Engineers Inc..
DOI: 10.1109/WACV45572.2020.9093343
Luo, Y., Wong, Y., Kankanhalli, M., Zhao, Q. (2020). G -Softmax: Improving Intraclass Compactness and Interclass Separability of Features. IEEE Transactions on Neural Networks and Learning Systems. 31 (2), [8712413]. [685-699].
DOI: 10.1109/TNNLS.2019.2909737