Zhiqiang Tao
Assistant Professor, School of Information
School of Information
Golisano College of Computing and Information Sciences
Office Location
Zhiqiang Tao
Assistant Professor, School of Information
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
Machine Learning
Computer Vision
Computational Imaging
Data Science
Select Scholarship
Journal Paper
Wang, Jiamian, et al. "S2-Transformer for Mask-Aware Hyperspectral Image Reconstruction." IEEE Transactions on Pattern Analysis and Machine Intelligence 47. 6 (2025): 4299-4316. Web.
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 36. 9 (2024): 4386--4397. Web.
Fang, Yi, Ashudeep Singh, and Zhiqiang Tao. "Fairness in Search Systems." Foundations and Trends in Information Retrieval 18. 3 (2024): 262-416. Print.
Published Conference Proceedings
Sun, Guohao, et al. "Structured Policy Optimization: Enhance Large Vision-Language Model via Self-Referenced Dialogue." Proceedings of the International Conference on Computer Vision (ICCV). Ed. N/A. Honolulu, Hawai'i: n.p., 2025. Web.
Sun, Guohao, et al. "Latent Chain-of-Thought for Visual Reasoning." Proceedings of the Thirty-Ninth Conference on Neural Information Processing Systems (NeurIPS 2025). Ed. n/a. San Diego, CA: n.p., Web.
Wang, Jiamian, et al. "Visual Self-Refinement for Autoregressive Models." Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025. Ed. Christos Christodoulopoulos, et al. Suzhou, China: n.p., Web.
Pulakurthi, Prasanna Reddy, et al. "X-CoT: Explainable Text-to-Video Retrieval via LLM-based Chain-of-Thought Reasoning." Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. Ed. Christos Christodoulopoulos, et al. Suzhou, China: 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, Jiamian, et al. "Diffusion-Inspired Truncated Sampler for Text-Video Retrieval." Proceedings of the Advances in Neural Information Processing Systems (NeurIPS). Ed. n/a. Vancouver, Canada: n.p., 2024. Web.
Wang, Jiamian, et al. "Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging." Proceedings of the Advances in Neural Information Processing Systems (NeurIPS). Ed. n/a. Vancouver, Canada: n.p., 2024. Web.
Sun, Guohao, et al. "SQ-LLaVA: Self-Questioning for Large Vision-Language Assistant." Proceedings of the European Conference on Computer Vision (ECCV). Ed. n/a. Milano, Italy: n.p., 2024. Web.
Sun, Guohao, et al. "Self-Training Large Language and Vision Assistant for Medical Question-Answering." Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP). Ed. n/a. Miami, FL: n.p., 2024. Web.
Wang, Jiamian, et al. "Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution." Proceedings of the International Conference on Computer Vision (ICCV). 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.
Currently Teaching
DSCI-633
Foundations of Data Science and Analytics
3 Credits
A foundations course in data science, emphasizing both concepts and techniques. The course provides an overview of data analysis tasks and the associated challenges, spanning data preprocessing, model building, model evaluation, and visualization. The major areas of machine learning, such as unsupervised, semi-supervised and supervised learning are covered by data analysis techniques including classification, clustering, association analysis, anomaly detection, and statistical testing. The course includes a series of assignments utilizing practical datasets from diverse application domains, which are designed to reinforce the concepts and techniques covered in lectures. A substantial project related to one or more data sets culminates the course.
IDAI-780
Capstone Project
3 Credits
Graduate capstone project by the candidate on an appropriate topic as arranged
between the candidate and the research advisor.
ISTE-782
Visual Analytics
3 Credits
This course introduces students to Visual Analytics, or the science of analytical reasoning facilitated by interactive visual interfaces. Course lectures, reading assignments, and practical lab experiences will cover a mix of theoretical and technical Visual Analytics topics. Topics include analytical reasoning, human cognition and perception of visual information, visual representation and interaction technologies, data representation and transformation, production, presentation, and dissemination of analytic process results, and Visual Analytic case studies and applications. Furthermore, students will learn relevant Visual Analytics research trends such as Space, Time, and Multivariate Analytics and Extreme Scale Visual Analytics.