Nathan Kallus

3.2k total citations · 1 hit paper
52 papers, 975 citations indexed

About

Nathan Kallus is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Nathan Kallus has authored 52 papers receiving a total of 975 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Statistics and Probability, 19 papers in Artificial Intelligence and 17 papers in Management Science and Operations Research. Recurrent topics in Nathan Kallus's work include Advanced Causal Inference Techniques (20 papers), Statistical Methods and Inference (13 papers) and Reinforcement Learning in Robotics (9 papers). Nathan Kallus is often cited by papers focused on Advanced Causal Inference Techniques (20 papers), Statistical Methods and Inference (13 papers) and Reinforcement Learning in Robotics (9 papers). Nathan Kallus collaborates with scholars based in United States and China. Nathan Kallus's co-authors include Dimitris Bertsimas, Vishal Gupta, Xiaojie Mao, Angela Zhou, Masatoshi Uehara, Ying Daisy Zhuo, Alexander Weinstein, Mac Johnson, Amjad Hussain and Richard A. Baum and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Diabetes Care.

In The Last Decade

Nathan Kallus

46 papers receiving 936 citations

Hit Papers

Data-driven robust optimization 2017 2026 2020 2023 2017 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Data-driven robust optimization
    2017 365 citations Dimitris Bertsimas, Nathan Kallus et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nathan Kallus United States 14 418 220 166 156 131 52 975
Vishal Gupta United States 10 403 1.0× 108 0.5× 190 1.1× 101 0.6× 103 0.8× 23 869
Chi-Bin Cheng Taiwan 19 329 0.8× 193 0.9× 107 0.6× 339 2.2× 133 1.0× 52 1.1k
Ahmad M. Alshamrani Saudi Arabia 14 157 0.4× 128 0.6× 91 0.5× 102 0.7× 59 0.5× 94 825
Kuo-Chen Hung Taiwan 18 430 1.0× 139 0.6× 122 0.7× 200 1.3× 182 1.4× 59 865
Ayşe Özmen Türkiye 17 303 0.7× 74 0.3× 113 0.7× 104 0.7× 77 0.6× 23 930
Jing–Rong Chang Taiwan 13 629 1.5× 180 0.8× 210 1.3× 237 1.5× 34 0.3× 32 962
Grani A. Hanasusanto United States 12 505 1.2× 128 0.6× 301 1.8× 30 0.2× 109 0.8× 26 814
V.S.S. Yadavalli South Africa 19 150 0.4× 125 0.6× 73 0.4× 128 0.8× 262 2.0× 115 1.0k
Cécile Murat France 12 421 1.0× 85 0.4× 310 1.9× 59 0.4× 111 0.8× 30 1.1k
Savaş Dayanik United States 15 468 1.1× 168 0.8× 76 0.5× 260 1.7× 85 0.6× 34 1.1k

Countries citing papers authored by Nathan Kallus

Since Specialization
Citations

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

Fields of papers citing papers by Nathan Kallus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nathan Kallus

This figure shows the co-authorship network connecting the top 25 collaborators of Nathan Kallus. A scholar is included among the top collaborators of Nathan Kallus 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 Nathan Kallus. Nathan Kallus 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.
Zhu, Yaochen, et al.. (2025). Collaborative Retrieval for Large Language Model-based Conversational Recommender Systems. 3323–3334. 2 indexed citations
2.
Wang, Lequn, et al.. (2024). Off-Policy Evaluation for Large Action Spaces via Policy Convolution. 3576–3585. 1 indexed citations
3.
Bennett, Andrew & Nathan Kallus. (2023). The variational method of moments. Journal of the Royal Statistical Society Series B (Statistical Methodology). 85(3). 810–841. 2 indexed citations
4.
Kallus, Nathan & Michele Santacatterina. (2021). Optimal balancing of time-dependent confounders for marginal structural models. SHILAP Revista de lepidopterología. 9(1). 345–369. 5 indexed citations
5.
Pennicooke, Brenton, Michele Santacatterina, Jennifer Lee, Eric Elowitz, & Nathan Kallus. (2021). The effect of patient age on discharge destination and complications after lumbar spinal fusion. Journal of Clinical Neuroscience. 91. 319–326. 8 indexed citations
6.
Kallus, Nathan & Masatoshi Uehara. (2020). Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic Policies. Neural Information Processing Systems. 33. 10420–10430. 1 indexed citations
7.
Kallus, Nathan & Masatoshi Uehara. (2020). Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes. arXiv (Cornell University). 21(167). 1–63. 5 indexed citations
8.
Kallus, Nathan & Masatoshi Uehara. (2019). Efficiently Breaking the Curse of Horizon: Double Reinforcement Learning in Infinite-Horizon Processes.. arXiv (Cornell University). 7 indexed citations
9.
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
10.
Kallus, Nathan & Masatoshi Uehara. (2019). Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning. Neural Information Processing Systems. 32. 3325–3334. 3 indexed citations
11.
Kallus, Nathan & Angela Zhou. (2019). Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds. arXiv (Cornell University). 32. 3421–3432. 2 indexed citations
12.
Bennett, Andrew, Nathan Kallus, & Tobias Schnabel. (2019). Deep Generalized Method of Moments for Instrumental Variable Analysis. RePEc: Research Papers in Economics. 32. 3559–3569. 7 indexed citations
13.
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
14.
Kallus, Nathan & Angela Zhou. (2018). Policy Evaluation and Optimization with Continuous Treatments. International Conference on Artificial Intelligence and Statistics. 1243–1251. 4 indexed citations
15.
Kallus, Nathan. (2018). Instrument-Armed Bandits. 529–546. 3 indexed citations
16.
Kallus, Nathan. (2017). A Framework for Optimal Matching for Causal Inference. International Conference on Artificial Intelligence and Statistics. 372–381. 3 indexed citations
17.
Bertsimas, Dimitris & Nathan Kallus. (2016). Pricing from Observational Data. arXiv (Cornell University). 3 indexed citations
18.
Kallus, Nathan. (2014). From Predictions to Data-Driven Decisions Using Machine Learning.. arXiv (Cornell University). 2 indexed citations
19.
Baum, Richard A., Dimitris Bertsimas, & Nathan Kallus. (2014). Scheduling, Revenue Management, and Fairness in an Academic-Hospital Radiology Division. Academic Radiology. 21(10). 1322–1330. 21 indexed citations
20.
Kallus, Nathan. (2013). Regression-Robust Designs of Controlled Experiments. arXiv (Cornell University). 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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