Zhiqiang Tao Headshot

Zhiqiang Tao

Assistant Professor

School of Information
Golisano College of Computing and Information Sciences

Office Location

Zhiqiang Tao

Assistant Professor

School of Information
Golisano College of Computing and Information Sciences

Education

BE, Tianjin University (China); MS, Tianjin University (China); Ph.D., Northeastern University


Areas of Expertise

Select Scholarship

Published Conference Proceedings
Sun, Guohao, et al. "Aligning Out-of-Distribution Web Images and Caption Semantics via Evidential Learning." Proceedings of the ACM Web Conference (WWW). Ed. N/A. Sentosa, SINGAPORE: n.p., Web.
Wang, Jiamian, et al. "Text Is MASS: Modeling as Stochastic Embedding for Text-Video Retrieval." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Ed. N/A. Seattle, WA: n.p., Web.
Wang, Yuan, et al. "Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankers." Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). Ed. N/A. Mexico City, Mexico: n.p., Web.
Wang, Jiamian, et al. "Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution." Proceedings of the International Conference on Computer Vision. Ed. N/A. Paris, French: n.p., 2023. Print.
Wang, Yuan, et al. "An Empirical Study of Selection Bias in Pinterest Ads Retrieval." Proceedings of the Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023. Ed. Ambuj Singh, et al. Long Beach, CA: n.p., 2023. Web.
Sapkota, Hitesh, et al. "Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training." Proceedings of the Advances in Neural Information Processing Systems 36 (NeurIPS 2023). Ed. N/A. New Orleans, LA: n.p., Print.
Bai, Yue, et al. "Parameter-Efficient Masking Networks." Proceedings of the Advances in Neural Information Processing Systems 35 (NeurIPS 2022), Nov 2022, New Orleans. Ed. Alice H. Oh, et al. New Orleans, LA: Curran Associates, Inc., Print.
Yang, Xueying, et al. "Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty." Proceedings of the Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Oct, 2022, Atlanta, GA, USA. Ed. Mohammad Al Hasan and Li Xiong. Atlanta, GA, USA: Association for Computing Machinery, Print.
Journal Paper
Wang, Yuan, Zhiqiang Tao, and Yi Fang. "A Unified Meta-learning Framework for Fair Ranking with Curriculum Learning." IEEE Transactions on Knowledge and Data Engineering. (2024): PrePrints pp. 1-12,. Web.
Wang, Qianqian, et al. "Multi-View Subspace Clustering via Structured Multi-Pathway Network." IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS. (2022): 1-7. Print.

Currently Teaching

ISTE-612
3 Credits
This course provides students with exposure to foundational data analytics technologies, focusing on unstructured data. Topics include unstructured data modeling, indexing, retrieval, text classification, text clustering, and information visualization.
ISTE-780
3 Credits
Rapidly expanding collections of data from all areas of society are becoming available in digital form. Computer-based methods are available to facilitate discovering new information and knowledge that is embedded in these collections of data. This course provides students with an introduction to the use of these data analytic methods, with a focus on statistical learning models, within the context of the data-driven knowledge discovery process. Topics include motivations for data-driven discovery, sources of discoverable knowledge (e.g., data, text, the web, maps), data selection and retrieval, data transformation, computer-based methods for data-driven discovery, and interpretation of results. Emphasis is placed on the application of knowledge discovery methods to specific domains.