陈傲，男，中国矿业大学计算机学院准聘副教授。2025年于中国科学技术大学计算机学院获工学博士学位，主要从事机器学习、时间序列、异常诊断等领域的研究。
近年来，围绕复杂结构时序数据的异常检测问题，以第一作者身份在TPAMI、AAAI等国际期刊、会议上发表4篇论文；申请发明专利2项。参与包括科技部重大研究计划在内等多项科研项目。
代表性著作：
1. Ao Chen, Xiren Zhou, Yizhan Fan, and Huanhuan Chen. “Underground Diagnosis Based on GPR and Learning in the Model Space”. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 46: 3832- 3844, 2024.
2. Ao Chen, Xiren Zhou, Huanhuan Chen. “Efficient Anomaly Detection of Irregular Sequences in Ct-Echo Model Space”. 39th AAAI Conference on Artificial Intelligence (AAAI-25), 39(15): 15731–15739, 2025.
3. Ao Chen, Xiren Zhou, Yizhan Fan, Huanhuan Chen. “Anomaly Detection in Multi-Level Model Space”. IEEE Transactions on Big Data (TBD), 2025.
4. Ao Chen, Xiren Zhou, Huaijun Li, Danyang Zhao, Huanhuan Chen. “Sparse Model-Space Learning for Multivariate Sequence Classification”. 2024 10th International Conference on Big Data and Information Analytics (BigDIA), 105–111, 2024.
邮箱：chenao57@cumt.edu.cn
