杨毅，博士，硕士生导师。现任合肥工业大学计算机与信息学院讲师。于2020年在奥克兰理工大学获得博士学位，并于2022年起任职于合肥工业大学。研究方向主要包括人工智能安全、大语言模型与计算机视觉。在相关领域已发表高水平学术论文20余篇。担任IEEE TIFS、Pattern Recognition、Neural Networks等国际期刊以及AAAI、ACM MM、ICLR等国际会议的审稿人，并曾担任PRICAI 2022的宣传主席。主持安徽省重点实验室开放课题及企业横向课题等多项科研项目。指导学生获得省级竞赛奖项多项，大创省级/校级项目多项。

谷歌学术:https://scholar.google.com/citations?user=NmKxdooAAAAJ&hl=en

面向2026级硕士研究生：我们欢迎有志于在以下前沿领域深造的同学（2026年9月入学）提前联系。

• 神经网络后门攻防 (计划招收 1-2 名)

• 计算机视觉/图像鉴伪 (计划招收 1 名)

• 大语言模型 (计划招收 1 名)

对以上方向感兴趣或具备相关基础的同学，请将简历发送至邮箱 yyang@hfut.edu.cn。优秀者可提前加入团队，参与学术交流与项目研讨。

联系方式：合肥工业大学翡翠校区 科教楼 A602，yyang@hfut.edu.cn

部分论文成果：

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

[2] 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.

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

[4] 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.

[5] 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.

[6] 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.

[7] 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.

[8] 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.

[9] 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.

[10] 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).

[11] 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).

[12] 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