教师简介
赵知临，副教授、博士生导师、国家级高层次青年人才
研究领域
我们的研究主要聚焦于 机器学习，特别关注模型在未知环境中的行为与泛化能力，追求 大道至简 的研究理念，注重理论与实践的结合，致力于在算法原理与现实应用之间架起桥梁。当前研究方向包括但不限于：
- 机器学习基础：外分布泛化、鲁棒性优化、不确定性建模、时序分析等
- 生成模型：图像生成、可控生成、图像编辑、生成对比学习等
- 大语言模型：检索增强生成、幻觉检测与校正、跨语言与跨任务迁移
- 具身智能与多智能体系统：虚实迁移与策略适应、语言驱动的具身操作、多智能体协同与决策等
- 自由探索：如果你有自己的研究兴趣，也欢迎提出，我们可以一起学习、共同深入
👉 点击这里查看我们团队的介绍。
📌 实验室拥有众多计算资源供组内使用。如果您对我的研究方向感兴趣，并希望与我共同学习与探索，欢迎博士生、硕士生以及优秀本科生加入实验室。
📢 目前有2026年入学的专业硕士、学术硕士、学术博士、深圳河套学院联培博士名额，如有意向，请随时与我联系。
获奖及荣誉
2018 广东省优秀硕士毕业生
2016 中山大学优秀本科毕业生
教育背景
2018.8-2022.8，悉尼科技大学，工程与信息技术学院，博士
2016.9-2018.6，中山大学，计算机学院，硕士
2012.9-2016.6，中山大学，计算机学院，学士
工作经历
2024.12至今，中山大学，计算机学院，副教授
2023.5-2024.11，麦考瑞大学，科学与工程学院，博士后
2022.8-2023.5，悉尼科技大学，工程与信息技术学院，博士后
代表性论著
[TPAMI] Zhilin Zhao, Longbing Cao, Yixuan Zhang, Kun-Yu Lin, Wei-Shi Zheng. Distilling the Unknown to Unveil Certainty. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.
[TPAMI] Zhilin Zhao, Longbing Cao, Kun-Yu Lin. Supervision Adaptation Balancing In-Distribution Generalization and Out-of-Distribution Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 12, pp. 15743-15758, 2023.
[TPAMI] Zhilin Zhao, Longbing Cao, Kun-Yu Lin. Revealing the Distributional Vulnerability of Discriminators by Implicit Generators. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 7, pp. 8888-8901, 2022.
[AI] Zhilin Zhao, Longbing Cao, Philip S. Yu. Out-of-distribution Detection by Regaining Lost Clues. Artificial Intelligence，vol. 339, pp. 104275, 2024.
[TMLR] Zhilin Zhao, Longbing Cao. Dual Representation Learning for Out-of-Distribution Detection. Transactions on Machine Learning Research, pp. 1-21, 2023.
[ML] Zhilin Zhao, Longbing Cao. Weighting Non-IID Batches for Out-of-distribution Detection. Machine Learning, vol. 113, no. 10, pp. 7371-7391, 2024.
[TNNLS] Zhilin Zhao, Longbing Cao, Kun-Yu Lin. Out-of-Distribution Detection by Cross-Class Vicinity Distribution of In-Distribution Data. IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 10, pp. 13777-13788, 2024.
[TNNLS] Zhilin Zhao, Longbing Cao, Chang-Dong Wang. Gray Learning from Non-iid Data with Out-of-distribution Samples. IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 1, pp. 1396-1409, 2025.
[NeurIPS] Zhilin Zhao，Longbing Cao, Xuhui Fan, Wei-Shi Zheng. Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data. Advances in Neural Information Processing Systems, pp. 1-28, 2024.
[NeurIPS] Zhilin Zhao，Longbing Cao. R-divergence for Estimating Model-oriented Distribution Discrepancy. Advances in Neural Information Processing Systems, pp. 1-19, 2023.
[AAAI] Zhilin Zhao, Longbing Cao, Yuanyu Wan. Mixture of Online and Offline Experts for Non-stationary Time Series. Association for the Advancement of Artificial Intelligence, pp. 1-8，2025.
[IJCAI] Zhilin Zhao, Longbing Cao, Philip S. Yu. Out-of-distribution Detection by Regaining Lost Clues. International Joint Conference on Artificial Intelligence，2025.
