Stefan Wager

6.2k total citations · 1 hit paper
60 papers, 2.2k citations indexed

About

Stefan Wager is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Stefan Wager has authored 60 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Statistics and Probability, 12 papers in Artificial Intelligence and 10 papers in Computer Networks and Communications. Recurrent topics in Stefan Wager's work include Statistical Methods and Inference (21 papers), Advanced Causal Inference Techniques (18 papers) and Statistical Methods and Bayesian Inference (12 papers). Stefan Wager is often cited by papers focused on Statistical Methods and Inference (21 papers), Advanced Causal Inference Techniques (18 papers) and Statistical Methods and Bayesian Inference (12 papers). Stefan Wager collaborates with scholars based in United States, Finland and Switzerland. Stefan Wager's co-authors include Susan Athey, Percy Liang, Sida Wang, Robert Tibshirani, Trevor Hastie, Max G’Sell, Alexandra Chouldechova, Jonathan Taylor, Emma Brunskill and Suzanne de Treville and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Statistical Association and PLoS ONE.

In The Last Decade

Stefan Wager

55 papers receiving 2.1k citations

Hit Papers

Estimation and Inference of Heterogeneous Treatment Effec... 2017 2026 2020 2023 2017 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stefan Wager United States 15 833 471 421 191 164 60 2.2k
Alexandre Belloni United States 23 1.5k 1.8× 1.0k 2.1× 437 1.0× 361 1.9× 293 1.8× 60 3.5k
Hrishikesh D. Vinod United States 27 661 0.8× 905 1.9× 352 0.8× 346 1.8× 156 1.0× 144 3.1k
Denis Chetverikov United States 16 1.3k 1.6× 711 1.5× 339 0.8× 187 1.0× 163 1.0× 27 2.4k
Han Liu China 17 257 0.3× 270 0.6× 314 0.7× 144 0.8× 304 1.9× 57 1.8k
Xinyuan Song China 28 1.3k 1.5× 219 0.5× 607 1.4× 265 1.4× 108 0.7× 144 2.8k
Kuldeep Kumar Australia 24 221 0.3× 332 0.7× 486 1.2× 310 1.6× 151 0.9× 179 2.6k
Stan Lipovetsky United States 24 718 0.9× 310 0.7× 435 1.0× 1.0k 5.3× 124 0.8× 194 3.0k
Göran Kauermann Germany 24 933 1.1× 497 1.1× 247 0.6× 195 1.0× 149 0.9× 131 2.3k
Sangit Chätterjee United States 18 225 0.3× 337 0.7× 236 0.6× 160 0.8× 123 0.8× 75 1.6k

Countries citing papers authored by Stefan Wager

Since Specialization
Citations

This map shows the geographic impact of Stefan Wager'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 Stefan Wager with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Wager more than expected).

Fields of papers citing papers by Stefan Wager

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stefan Wager. 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 Stefan Wager. The network helps show where Stefan Wager may publish in the future.

Co-authorship network of co-authors of Stefan Wager

This figure shows the co-authorship network connecting the top 25 collaborators of Stefan Wager. A scholar is included among the top collaborators of Stefan Wager 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 Stefan Wager. Stefan Wager is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Petukhova, Maria, et al.. (2025). Estimating Treatment Effect Heterogeneity in Psychiatry: A Review and Tutorial With Causal Forests. International Journal of Methods in Psychiatric Research. 34(2). e70015–e70015. 4 indexed citations
2.
Wu, Han, et al.. (2024). Qini Curves for Multi-Armed Treatment Rules. Journal of Computational and Graphical Statistics. 34(3). 948–960. 4 indexed citations
3.
Zainal, Nur Hani, Robert M. Bossarte, Irving Hwang, et al.. (2024). Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records. Molecular Psychiatry. 29(8). 2335–2345. 3 indexed citations
4.
Haslinger, Christian, et al.. (2024). What makes forest-based heterogeneous treatment effect estimators work?. The Annals of Applied Statistics. 18(1). 2 indexed citations
5.
Wu, Xiao, et al.. (2023). Low-intensity fires mitigate the risk of high-intensity wildfires in California’s forests. Science Advances. 9(45). eadi4123–eadi4123. 21 indexed citations
6.
Ross, Eric L., Robert M. Bossarte, Steven K. Dobscha, et al.. (2023). Estimated Average Treatment Effect of Psychiatric Hospitalization in Patients With Suicidal Behaviors. JAMA Psychiatry. 81(2). 135–135. 10 indexed citations
7.
Gur, Yonatan, Ahmadreza Momeni, & Stefan Wager. (2019). Smoothness-Adaptive Stochastic Bandits.. arXiv (Cornell University).
8.
Ignatiadis, Nikolaos & Stefan Wager. (2019). Covariate-Powered Empirical Bayes Estimation. Neural Information Processing Systems. 32. 9620–9632. 2 indexed citations
9.
Wager, Stefan & Susan Athey. (2017). Estimation and Inference of Heterogeneous Treatment Effects using Random Forests. Journal of the American Statistical Association. 113(523). 1228–1242. 1346 indexed citations breakdown →
10.
Hirshberg, David A. & Stefan Wager. (2017). Balancing Out Regression Error: Efficient Treatment Effect Estimation without Smooth Propensities. arXiv (Cornell University).
11.
Wager, Stefan, et al.. (2017). Learning Objectives for Treatment Effect Estimation. arXiv (Cornell University). 11 indexed citations
12.
Nagata, Jason M., et al.. (2016). Prevalence and Predictors of Malnutrition among Guatemalan Children at 2 Years of Age. PLoS ONE. 11(11). e0164772–e0164772. 8 indexed citations
13.
Steinhardt, Jacob, Gregory Valiant, & Stefan Wager. (2015). Memory, Communication, and Statistical Queries. Electronic colloquium on computational complexity. 22. 126–1516. 2 indexed citations
14.
Wager, Stefan, et al.. (2014). Quantifying and Exploiting the Age Dependence in the Effect of Supplementary Food for Child Undernutrition. PLoS ONE. 9(6). e99632–e99632. 9 indexed citations
15.
G’Sell, Max, Stefan Wager, Alexandra Chouldechova, & Robert Tibshirani. (2013). False Discovery Rate Control for Sequential Selection Procedures, with Application to the Lasso. arXiv (Cornell University). 4 indexed citations
16.
Wager, Stefan, Trevor Hastie, & Bradley Efron. (2013). Standard Errors for Bagged Predictors and Random Forests. arXiv (Cornell University). 3 indexed citations
17.
Wang, Sida, Mengqiu Wang, Stefan Wager, Percy Liang, & Christopher D. Manning. (2013). Feature Noising for Log-Linear Structured Prediction. 1170–1179. 11 indexed citations
18.
Wager, Stefan, et al.. (2012). Cell range extension in LTE in-band relays: Analysis of radio link, subframe allocation and protocol perfornance of FTP traffic model. European Wireless Conference. 1–6. 3 indexed citations
19.
Chakraborty, S.S. & Stefan Wager. (1995). INHIBIT SENSE MULTIPLE ACCESS WITH POLLING : A MEDIA ACCESS CONTROL SCHEME FOR THE MOBILE ENVIRONMENT , AND ITS ADAPTATION TO THE GSM GENERAL PACKET RADIO SERVICES. Asia-Pacific Conference on Communications. 926–930. 3 indexed citations
20.
Chakraborty, S.S. & Stefan Wager. (1995). Inhibit Sense Multiple Access with Reservation, a Contender for GSM/GPRS Packet Services. 1 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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