Xiaojie Mao

595 total citations
13 papers, 141 citations indexed

About

Xiaojie Mao is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Xiaojie Mao has authored 13 papers receiving a total of 141 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Statistics and Probability, 4 papers in Artificial Intelligence and 3 papers in Management Science and Operations Research. Recurrent topics in Xiaojie Mao's work include Advanced Causal Inference Techniques (4 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers) and Statistical Methods and Inference (3 papers). Xiaojie Mao is often cited by papers focused on Advanced Causal Inference Techniques (4 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers) and Statistical Methods and Inference (3 papers). Xiaojie Mao collaborates with scholars based in United States and China. Xiaojie Mao's co-authors include Nathan Kallus, Angela Zhou, Madeleine Udell, Masatoshi Uehara, Tianqi Li, Bo Li, Ninghui Sun, Bowen Shi, Danni Liu and Mochen Yang and has published in prestigious journals such as Management Science, Operations Research and Journal of the Royal Statistical Society Series B (Statistical Methodology).

In The Last Decade

Xiaojie Mao

11 papers receiving 132 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Xiaojie Mao United States	6	40	35	31	28	20	13	141
Daniel Wilhelm United Kingdom	7	16 0.4×	16 0.5×	6 0.2×	35 1.3×	40 2.0×	20	164
Seth Neel United States	7	92 2.3×	19 0.5×	45 1.5×	4 0.1×	10 0.5×	12	119
Andrés Muñoz Medina United States	8	78 1.9×	84 2.4×	8 0.3×	4 0.1×	4 0.2×	15	161
Bo Waggoner United States	6	70 1.8×	79 2.3×	9 0.3×	3 0.1×	18 0.9×	20	138
Somit Gupta United States	7	23 0.6×	12 0.3×	4 0.1×	48 1.7×	6 0.3×	11	149
Peter Martey Addo France	5	109 2.7×	35 1.0×	5 0.2×	2 0.1×	64 3.2×	9	253
Nasim Sonboli United States	7	77 1.9×	59 1.7×	34 1.1×	4 0.1×	4 0.2×	16	177
Ashudeep Singh United States	4	57 1.4×	50 1.4×	13 0.4×	10 0.4×	8 0.4×	7	103
Antonio Maturo Italy	7	35 0.9×	48 1.4×		24 0.9×	10 0.5×	35	148
Yaron Shaposhnik United States	5	58 1.4×	28 0.8×	4 0.1×	4 0.1×	7 0.3×	15	114

Countries citing papers authored by Xiaojie Mao

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Xiaojie Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaojie Mao. A scholar is included among the top collaborators of Xiaojie Mao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiaojie Mao. Xiaojie Mao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

Shi, Bowen, Xiaojie Mao, Mochen Yang, & Bo Li. (2025). What, Why, and How: An Empiricist’s Guide to Double/Debiased Machine Learning. Information Systems Research.

Wang, Jiao, et al.. (2024). 17β-estradiol Inhibits Oxidative Stress-Induced Apoptosis in Endometrial Cancer Cells by Promoting FOXM1 Expression. Cell Biochemistry and Biophysics. 82(2). 1243–1251.

Kallus, Nathan & Xiaojie Mao. (2024). On the role of surrogates in the efficient estimation of treatment effects with limited outcome data. Journal of the Royal Statistical Society Series B (Statistical Methodology). 87(2). 480–509. 2 indexed citations

Liu, Danni, et al.. (2023). Efficiency Enhancing Technique for Rod Fiber Picosecond Amplifiers with Optimal Mode Field Matching. Micromachines. 14(2). 450–450. 1 indexed citations

Mao, Xiaojie, et al.. (2022). Dysregulation of Serum miR-138-5p and Its Clinical Significance in Patients with Acute Cerebral Infarction. Cerebrovascular Diseases. 51(5). 670–677. 5 indexed citations

Mao, Xiaojie, et al.. (2022). Smooth Contextual Bandits: Bridging the Parametric and Nondifferentiable Regret Regimes. Operations Research. 70(6). 3261–3281. 5 indexed citations

Kallus, Nathan, et al.. (2022). Fast Rates for Contextual Linear Optimization. Management Science. 68(6). 4236–4245. 17 indexed citations

Kallus, Nathan & Xiaojie Mao. (2022). Stochastic Optimization Forests. Management Science. 69(4). 1975–1994. 27 indexed citations

Kallus, Nathan, Xiaojie Mao, & Angela Zhou. (2021). Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. Management Science. 68(3). 1959–1981. 39 indexed citations

10.

Kallus, Nathan, Xiaojie Mao, & Angela Zhou. (2020). Assessing algorithmic fairness with unobserved protected class using data combination. 110–110. 27 indexed citations

11.

Kallus, Nathan, Xiaojie Mao, & Masatoshi Uehara. (2019). Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond.. arXiv (Cornell University). 3 indexed citations

12.

Kallus, Nathan, Xiaojie Mao, & Madeleine Udell. (2018). Causal Inference with Noisy and Missing Covariates via Matrix Factorization. Neural Information Processing Systems. 31. 6921–6932. 2 indexed citations

13.

Kallus, Nathan, Xiaojie Mao, & Angela Zhou. (2018). Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. arXiv (Cornell University). 2281–2290. 13 indexed citations

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.

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