Department of Computer Science & Technology
Tsinghua University
East Main Building, Tsinghua University, Beijing, China, 100084
Email: lizhihan17 (at) mails.tsinghua.edu.cn
Education
- 09.2017 – now: Tsinghua University, a Ph.D.
- 09.2013 – 06.2017: Bachelor of Software engineering, Xidian University.
Research Interests
AIOps (AI for IT Operations), mainly focusing on time series anomaly detection, clustering.
Machine Learning, mainly focusing on deep generative models like VAEs.
Publications
- Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding
Zhihan Li, Youjian Zhao, Jiaqi Han, Ya Su, Rui Jiao, Xidao Wen, Dan Pei
KDD 2021, August 14-18, 2021, virtual conference
PaperSlidesVideoCode - Shallow VAEs with RealNVP Prior Can Perform as Well as Deep Hierarchical VAEs
Haowen Xu, Wenxiao Chen, Jinlni Lai, Zhihan Li, Youjian Zhao, Dan Pei
ICONIP2020, November 18 – 22, 2020, Online
PaperSlides - Unsupervised Clustering through Gaussian Mixture Variational AutoEncoder with Non-Reparameterized Variational Inference and Std Annealing
Zhihan Li, Youjian Zhao, Haowen Xu, Wenxiao Chen, Shangqing Xu, Yilin Li, Dan Pei
IJCNN (WCCI) 2020, Virtual Conference, Jul 19-24, 2020
PaperSlidesVideo - Dynamic TCP Initial Windows and Congestion Control Schemes through Reinforcement Learning
Xiaohui Nie, Youjian Zhao, Zhihan li, Guo Chen, Kaixin Sui, Jiyang Zhang, Zijie Ye, Dan Pei
JSAC 2019, Artificial Intelligence and Machine Learning for Networking and Communications
Paper (A journal paper, no slides) - Robust and Rapid Clustering of KPIs for Large-Scale Anomaly Detection
Zhihan Li, Youjian Zhao, Rong Liu, Dan Pei
IWQoS 2018, Banff, Alberta, Canada, June 4-6, 2018.
Paper Slides - Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
Haowen Xu, Wenxiao Chen, Nengwen Zhao, Zeyan Li, Jiahao Bu, Zhihan Li, Ying Liu, Youjian Zhao, Dan Pei, Yang Feng, Jie Chen, Zhaogang Wang and Honglin Qiao
WWW 2018, Lyon, France, 23-27 April 2018
PaperSlidesCode