Pasin Manurangsi

1.1k total citations
47 papers, 252 citations indexed

About

Pasin Manurangsi is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Pasin Manurangsi has authored 47 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computational Theory and Mathematics, 20 papers in Artificial Intelligence and 19 papers in Economics and Econometrics. Recurrent topics in Pasin Manurangsi's work include Complexity and Algorithms in Graphs (22 papers), Game Theory and Voting Systems (18 papers) and Advanced Graph Theory Research (13 papers). Pasin Manurangsi is often cited by papers focused on Complexity and Algorithms in Graphs (22 papers), Game Theory and Voting Systems (18 papers) and Advanced Graph Theory Research (13 papers). Pasin Manurangsi collaborates with scholars based in United States, Singapore and United Kingdom. Pasin Manurangsi's co-authors include Warut Suksompong, Xiaohui Bei, Ravi Kumar, Bundit Laekhanukit, Rajesh Chitnis, Andreas Emil Feldmann, Piotr Faliszewski, Adrià Gascón, Parinya Chalermsook and Aravindan Vijayaraghavan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Artificial Intelligence and Journal of the ACM.

In The Last Decade

Pasin Manurangsi

42 papers receiving 241 citations

Peers

Pasin Manurangsi

CTM

EE

MSOR

AI

CNC

Saeed Seddighin United States

Eric Balkanski United States

Ami Paz Israel

Yasushi Kawase Japan

Ildikó Schlotter Hungary

Claire Kenyon-Mathieu United States

Manuel Sorge Germany

Jack M. Robertson United States

Nima Anari United States

Iftah Gamzu Israel

Saeed Seddighin United States

Pasin Manurangsi

50 ×0.5

CTM

106 ×1.2

EE

108 ×1.4

MSOR

44 ×0.7

AI

32 ×0.7

CNC

Citations per year, relative to Pasin Manurangsi Pasin Manurangsi (= 1×) peers Saeed Seddighin

Countries citing papers authored by Pasin Manurangsi

Since Specialization

Citations

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

Fields of papers citing papers by Pasin Manurangsi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pasin Manurangsi

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

All Works

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20 of 20 papers shown

1.

Aksu, Hidayet, Badih Ghazi, Pritish Kamath, et al.. (2024). Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API. Proceedings on Privacy Enhancing Technologies. 2024(4). 605–621. 1 indexed citations

2.

Manurangsi, Pasin, et al.. (2024). Differentially Private Ad Conversion Measurement. Proceedings on Privacy Enhancing Technologies. 2024(2). 124–140.

3.

Kamath, Pritish, et al.. (2024). Differentially Private Optimization with Sparse Gradients. 63406–63440.

4.

Kumar, Ravi, et al.. (2023). Differentially Private Data Release over Multiple Tables. 207–219. 1 indexed citations

5.

Manurangsi, Pasin & Warut Suksompong. (2023). Differentially Private Fair Division. Proceedings of the AAAI Conference on Artificial Intelligence. 37(5). 5814–5822. 3 indexed citations

6.

Kohlhoff, Kai, et al.. (2023). Differentially Private Heatmaps. Proceedings of the AAAI Conference on Artificial Intelligence. 37(6). 7696–7704. 3 indexed citations

7.

Kumar, Ravi, et al.. (2021). User-Level Differentially Private Learning via Correlated Sampling. Neural Information Processing Systems. 34. 3 indexed citations

8.

Chitnis, Rajesh, Andreas Emil Feldmann, & Pasin Manurangsi. (2021). Parameterized Approximation Algorithms for Bidirected Steiner Network Problems. ACM Transactions on Algorithms. 17(2). 1–68. 4 indexed citations

9.

Bei, Xiaohui, et al.. (2021). The Price of Fairness for Indivisible Goods. Theory of Computing Systems. 65(7). 1069–1093. 14 indexed citations

10.

Manurangsi, Pasin & Warut Suksompong. (2021). Generalized Kings and Single-Elimination Winners in Random Tournaments. 328–334. 1 indexed citations

11.

Golowich, Noah, et al.. (2020). Pure Differentially Private Summation from Anonymous Messages. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 1 indexed citations

12.

Kumar, Ravi, et al.. (2020). Differentially Private Clustering: Tight Approximation Ratios. Neural Information Processing Systems. 33. 4040–4054. 2 indexed citations

13.

Manurangsi, Pasin, et al.. (2019). On Closest Pair in Euclidean Metric: Monochromatic is as Hard as Bichromatic. arXiv (Cornell University). 16. 2 indexed citations

14.

Gupta, Anupam, et al.. (2019). Losing tree-width by separating subsets. Symposium on Discrete Algorithms. 1731–1749. 1 indexed citations

15.

Bei, Xiaohui, et al.. (2019). The Price of Fairness for Indivisible Goods. 81–87. 14 indexed citations

16.

Laekhanukit, Bundit, et al.. (2019). On the Parameterized Complexity of Approximating Dominating Set. Journal of the ACM. 66(5). 1–38. 6 indexed citations

17.

Faliszewski, Piotr, et al.. (2019). Approximation and Hardness of Shift-Bribery. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 1901–1908. 6 indexed citations

18.

Chitnis, Rajesh, Andreas Emil Feldmann, & Pasin Manurangsi. (2018). Parameterized Approximation Algorithms for Bidirected Steiner Network Problems. Warwick Research Archive Portal (University of Warwick). 16. 4 indexed citations

19.

Manurangsi, Pasin & Warut Suksompong. (2018). Computing a small agreeable set of indivisible items. Artificial Intelligence. 268. 96–114. 6 indexed citations

20.

Manurangsi, Pasin, Preetum Nakkiran, & Luca Trevisan. (2016). Near-Optimal UGC-hardness of Approximating Max k-CSP_R. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 28. 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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