Xiaojie Mao
- Safety Research top 10%
- Statistics and Probability top 10%
- Advanced Causal Inference Techniques 4
- Statistical Methods and Inference 3
- Statistical Methods and Bayesian Inference 2
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- Advanced Bandit Algorithms Research 3
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- Health Systems, Economic Evaluations, Quality of Life 3
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- Distributed Sensor Networks and Detection Algorithms 1
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- Bayesian Modeling and Causal Inference 1
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- Genomics, phytochemicals, and oxidative stress 1
- Co-authors
- Nathan KallusAngela ZhouMadeleine UdellMasatoshi UeharaTianqi LiBo LiNinghui SunBowen Shi
- Journals
- Management Science (3 papers)Operations Research (1 paper)Journal of the Royal Statistical Society Series B (Statistical Methodology) (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Xiaojie Mao
11 papers receiving 132 citations
Peers
Comparison fields: 5 of 56
- Health Informatics 6
- Safety Research 31
- Statistics and Probability 28
- Management Science and Operations Research 35
- Management Information Systems 18
Countries citing papers authored by Xiaojie Mao
This map shows the geographic impact of Xiaojie Mao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiaojie Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojie Mao more than expected).
Fields of papers citing papers by Xiaojie Mao
This network shows the impact of papers produced by Xiaojie Mao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiaojie Mao. The network helps show where Xiaojie Mao may publish in the future.
Co-authorship network
The 11 scholars most cited alongside Xiaojie Mao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 1 | |
| 5 | 2022 | 5 | |
| 6 | 2022 | 5 | |
| 7 | 2022 | 17 | |
| 8 | 2022 | 27 | |
| 9 | 2021 | 39 | |
| 10 | 2020 | 27 | |
| 11 | Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond. | 2019 | 3 |
| 12 | Causal Inference with Noisy and Missing Covariates via Matrix Factorization | 2018 | 2 |
| 13 | 2018 | 13 |
About Xiaojie Mao
Xiaojie Mao is a scholar working on Statistics and Probability, Management Science and Operations Research and Artificial Intelligence, having authored 13 papers that have together received 141 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (4 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers), Statistical Methods and Inference (3 papers), Advanced Bandit Algorithms Research (3 papers), Statistical Methods and Bayesian Inference (2 papers), Distributed Sensor Networks and Detection Algorithms (1 paper), Bayesian Modeling and Causal Inference (1 paper) and Genomics, phytochemicals, and oxidative stress (1 paper). The work is most often cited by research in Health Informatics (6 citations), Safety Research (31 citations) and Statistics and Probability (28 citations). Xiaojie Mao has collaborated with scholars based in United States and China. Frequent co-authors include Nathan Kallus, Angela Zhou, Madeleine Udell, Masatoshi Uehara, Tianqi Li, Bo Li, Ninghui Sun, Bowen Shi, Danni Liu and Mochen Yang. Their work appears in journals such as Management Science, Operations Research and Journal of the Royal Statistical Society Series B (Statistical Methodology).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.