杨毅，博士，硕士生导师。研究方向包括AI安全、计算机视觉、众包真值推断，已发表高水平论文20余篇。2020年在奥克兰理工大学获得博士学位。2022年起在任合肥工业大学计算机与信息学院任讲师。

部分论文成果：

Chen, R., Shen, H., Zhao, Z. Q., Yang, Y., & Zhang, Z. (2024). Global routing between capsules. Pattern Recognition, 148, 110142.

Yang, Y., Zhao, Z. Q., Wu, G., Zhuo, X., Liu, Q., Bai, Q., & Li, W. (2024). A Lightweight, Effective, and Efficient Model for Label Aggregation in Crowdsourcing. ACM Transactions on Knowledge Discovery from Data, 18(4), 1-27.

Shi, J., Li, W., Bai, Q., Yang, Y., & Jiang, J. (2023). Syntax-enhanced aspect-based sentiment analysis with multi-layer attention. Neurocomputing, 557, 126730.

Yao, N., Liu, Q., Yang, Y., Li, W., & Bai, Q. (2023, October). Entity-Relation Distribution-Aware Negative Sampling for Knowledge Graph Embedding. In International Semantic Web Conference (pp. 234-252). Cham: Springer Nature Switzerland.

Li, R., Li, W., Yang, Y., Wei, H., Jiang, J., & Bai, Q. (2023). Swinv2-imagen: Hierarchical vision transformer diffusion models for text-to-image generation. Neural Computing and Applications, 1-16.

Zheng, G., Zhao, Z., Zhang, Z., & Yang, Y. (2023, July). Hierarchical Graph Neural Network for Human Pose Estimation. In 2023 IEEE International Conference on Multimedia and Expo (ICME) (pp. 2663-2668). IEEE.

Yao, N., Liu, Q., Li, X., Yang, Y., & Bai, Q. (2022, November). Entity similarity-based negative sampling for knowledge graph embedding. In Pacific Rim International Conference on Artificial Intelligence (pp. 73-87). Cham: Springer Nature Switzerland.

Shi, J., Li, W., Yongchareon, S., Yang, Y., & Bai, Q. (2022). Graph-based joint pandemic concern and relation extraction on twitter. Expert Systems with Applications, 195, 116538.

Li, W., Bai, Q., Liang, L., Yang, Y., Hu, Y., & Zhang, M. (2021). Social influence minimization based on context-aware multiple influences diffusion model. Knowledge-Based Systems, 227, 107233.

Yang, Y., Bai, Q., & Liu, Q. (2019, May). Dynamic source weight computation for truth inference over data streams. In Proceedings of the 18th international conference on autonomous agents and multiagent systems (pp. 277-285).

Yang, Y., Bai, Q., & Liu, Q. (2019, May). Modeling random guessing and task difficulty for truth inference in crowdsourcing. In Proceedings of the 18th international conference on autonomous agents and multiagent systems (pp. 2288-2290).

Yang, Y., Bai, Q., & Liu, Q. (2019). A probabilistic model for truth discovery with object correlations. Knowledge-Based Systems, 165, 360-373.

[1] 2016.8 -- 2020.8
奥克兰理工大学       计算机科学与技术       研究生(博士)毕业       博士学位

[1] 2022.1 -- 至今
合肥工业大学      计算机与信息学院      讲师      在职