姓名：赵颖
职称：副研究员
电话：62783505-8006
邮件：yingz@tsinghua.edu.cn
教育背景
理学学士 (计算机科学), 北京大学, 中国, 1999;
博士 (计算机科学), 明尼苏达大学, 美国, 2005.
研究领域
数据挖掘, 机器学习
研究概况
长期从事数据挖掘与人工智能方面的研究，主持并参与多项国家自然基金、国家重点研发计划等科研项目。近年来主要研究方向为人工智能模型的不确定性以及地球系统模式发展中的关键人工智能技术。在人工智能模型的不确定性方面，首次给出了数据增强可用于对人工智能模型的模型不确定性进行建模的理论推导，同时开展人工智能与数值预报的深度融合方向的研究。在数据挖掘方面，主要研究时空数据的高效索引及访问技术，相关技术为北京2022冬奥气象保障任务提供了海量模式数据处理服务。
奖励与荣誉
《组合数学与算法设计》入选教育部来华留学生英语授课品牌课程 (2017)
深圳市海外高层次人才创新创业计划 (2012)
国家留学基金委: IBM奖研金 (2007)
学术成果
AI for Science
[1] Ziheng Zhou, Ying Zhao, Yiyu Qing, Wenming Jiang, Yihan Wu, Wenguang Chen. A Physics-guided NN-based Approach for Tropical Cyclone Intensity Estimation. Proceedings of the 2023 SIAM International Conference on Data Mining (SDM23), pp. 271–279, 2023.
[2] Wenming Jiang, Ying Zhao, Yihan Wu, Haojia Zuo. Capturing Model Uncertainty with Data Augmentation in Deep Learning. Proceedings of the 2022 SIAM International Conference on Data Mining (SDM22), pp. 271–279, 2022.
[3] Wenming Jiang, Ying Zhao, Zehan Wang. Risk-Controlled Selective Prediction for Regression Deep Neural Network Models. Proceedings of 2020 International Joint Conference on Neural Networks (IJCNN 2020), 2020.
Spatial-Temporal Data Mining
[4] Lohan Meunier, Ying Zhao. Reachability Queries on Dynamic Temporal Bipartite Graphs. Proceedings of the 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2023), accepted, Hamburg, Germany, 2023.
[5] Haojia Zuo, Bo Cao, Ying Zhao, Bilong Shen, Weimin Zheng, Yan Huang. High-capacity ride-sharing via shortest path clustering on large road networks. Journal of Supercomputing, 77(4), 4081-4106, 2021.
[6] Bilong Shen, Ying Zhao, Guoliang Li, Weimin Zheng, Yue Qin, Bo Yuan, Yongming Rao. V-Tree: Efficient kNN Search on Moving Objects with Road-Network Constraints. Proceedings of the 33th IEEE International Conference on Data Engineering (ICDE17), pp. 609-620, San Diego, USA, 2017.
Clustering
[7] Ying Zhao and George Karypis. Hierarchical Clustering Algorithms for Document Datasets. Data Mining and Knowledge Discovery, vol.10, no. 2, pp. 141-168, 2005.
[8] Ying Zhao and George Karypis. Topic-driven Clustering for Document Datasets. Proceedings of the 2005 SIAM International Conference on Data Mining (SDM05), pp. 358-369, 2005.
[9] Ying Zhao and George Karypis. Empirical and Theoretical Comparisons of Selected Criterion Functions for Document Clustering. Machine Learning, vol. 55, no. 3, pp. 311-331, 2004.
