Senior Researcher

Microsoft Research Asia

About Me

I am currently a senior researcher at Microsoft Research Asia (MSRA), Machine Learning Group, headed by Prof. Tie-Yan Liu. I received my Ph.D. degree from Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University in 2018, under the supervision of Prof. Jian Li. Before that, I received the B. Sc degree from Department of Computer Science at Wuhan University in 2013.

I have a wide range of research interests on applied machine learning, including Time Series Forecasting, Intelligent Health-Care, Logistics Optimization etc. In the past years, we co-worked with many leading companies in various fields to explore the opportunities of AI in the corresponding scenarios, including China-AMC, Shunfeng Tech, Humana and Sanofi, etc.

HIRING: I am seeking for self-motived interns who have interests on time series, tabular data and autoML. Feel free to contact me if you are interested.

Interests

Time Series Forecasting
Graph Neural Network
Intelligent Health-care

Education

PhD in Computer Science, 2018

Tsinghua University
BSc in Computer Science, 2013

Wuhan University

Experience

Senior Researcher

Microsoft Research Asia (MSRA)

Jul 2018 – Present Beijing

Research Intern

Bytedance, AI Lab

Jul 2017 – Oct 2017 Beijing

Research Intern

Didi Chuxing

Nov 2015 – Jan 2016 Beijing

Research Intern

Baidu, Bigdata Lab (BDL)

Mar 2015 – Aug 2015 Beijing

Software Dev Intern

Microsoft, Search Tech Center (STC)

Oct 2012 – Jul 2012 Beijing

Publications

Estee Y Cramer, Evan L Ray, Velma K Lopez, Johannes Bracher, Andrea Brennen, Alvaro J Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Katie H House, Yuxin Huang, others (2021). Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US. Proceedings of the National Academy of Sciences.

Shun Zheng, Zhifeng Gao, Wei Cao, Jiang Bian, Tie-Yan Liu (2021). HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting. Proceedings of the 30th ACM International Conference on Information & Knowledge Management.

Disheng Tang, Wei Cao, Jiang Bian, Tie-Yan Liu, Zhifeng Gao, Shun Zheng, Jue Liu (2021). Impact of pandemic fatigue on the spread of COVID-19: a mathematical modelling study. arXiv preprint arXiv:2104.04235.

Shun Zheng, Wei Cao, Wei Xu, Jiang Bian (2021). Revisiting the evaluation of end-to-end event extraction. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021.

Zhining Liu, Pengfei Wei, Zhepei Wei, Boyang Yu, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang (2021). Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning. arXiv preprint arXiv:2111.12791.

Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang (2020). MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. Advances in Neural Information Processing Systems.

Shun Zheng, Wei Cao, Wei Xu, Jiang Bian (2019). Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction. EMNLP.

Dong Wang, Yitong Li, Wei Cao, Liqun Chen, Qi Wei, Lawrence Carin (2019). LMVP: Video Predictor with Leaked Motion Information. NIPS Workshop.

Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu (2019). Self-paced Ensemble for Highly Imbalanced Massive Data Classification. ICDE.

Wei Cao, Dong Wang, Jian Li, Hao Zhou, Lei Li, Yitan Li (2018). BRITS: bidirectional recurrent imputation for time series. NIPS.

Dong Wang, Junbo Zhang, Wei Cao, Jian Li, Yu Zheng (2018). When will you arrive? estimating travel time based on deep neural networks. AAAI.

Dong Wang, Wei Cao, Jian Li, Jieping Ye (2017). DeepSD: supply-demand prediction for online car-hailing services using deep neural networks. ICDE.

Wei Cao, Jian Li, Haitao Wang, Kangning Wang, Ruosong Wang, Raymond Chi-Wing Wong, Wei Zhan (2017). k-regret minimizing set: Efficient algorithms and hardness. ICDT.

Wei Cao, Zhengwei Wu, Dong Wang, Jian Li, Haishan Wu (2016). Automatic user identification method across heterogeneous mobility data sources. ICDE.

Wei Cao, Jian Li, Shimin Li, Haitao Wang (2015). Balanced splitting on weighted intervals. Operations Research Letters.

Wei Cao, Jian Li, Yufei Tao, Zhize Li (2015). On top-k selection in multi-armed bandits and hidden bipartite graphs. NIPS.

Projects

COVID Forecasting

COVID Forecasting

We propose HierST, a hierarchical graph neural network for COVID situation forecasting. The forecasting results could be found on US-CDC website (model name: Microsoft)

Hobby

I am a big fan of sports (as well as my cute wife 😄), especially the cycling. I am a member of Tsinghua Cycling Club. You can find my strava here.