Yang P. Liu

537 total citations
20 papers, 152 citations indexed

About

Yang P. Liu is a scholar working on Computational Theory and Mathematics, Statistics and Probability and Artificial Intelligence. According to data from OpenAlex, Yang P. Liu has authored 20 papers receiving a total of 152 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computational Theory and Mathematics, 10 papers in Statistics and Probability and 7 papers in Artificial Intelligence. Recurrent topics in Yang P. Liu's work include Complexity and Algorithms in Graphs (14 papers), Markov Chains and Monte Carlo Methods (9 papers) and Optimization and Search Problems (5 papers). Yang P. Liu is often cited by papers focused on Complexity and Algorithms in Graphs (14 papers), Markov Chains and Monte Carlo Methods (9 papers) and Optimization and Search Problems (5 papers). Yang P. Liu collaborates with scholars based in United States, Switzerland and Canada. Yang P. Liu's co-authors include Aaron Sidford, Maximilian Probst Gutenberg, Rasmus Kyng, Sushant Sachdeva, Richard Peng, Li Chen, Jan van den Brand, Yufei Zhao, Di Wang and Yin Tat Lee and has published in prestigious journals such as Communications of the ACM, Journal of the ACM and SIAM Journal on Computing.

In The Last Decade

Yang P. Liu

15 papers receiving 149 citations

Peers

Yang P. Liu
Jan van den Brand United States
Thatchaphol Saranurak United States
Rishi Saket United States
Virginia Vassilevska United States
Arnab Bhattacharyya United States
Maximilian Probst Gutenberg Switzerland
Leonid Zosin Israel
Kevin Matulef United States
Stanislav Živný United Kingdom
Bruno Escoffier France
Jan van den Brand United States
Yang P. Liu
Citations per year, relative to Yang P. Liu Yang P. Liu (= 1×) peers Jan van den Brand

Countries citing papers authored by Yang P. Liu

Since Specialization
Citations

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

Fields of papers citing papers by Yang P. Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yang P. Liu. 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 Yang P. Liu. The network helps show where Yang P. Liu may publish in the future.

Co-authorship network of co-authors of Yang P. Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Yang P. Liu. A scholar is included among the top collaborators of Yang P. Liu 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 Yang P. Liu. Yang P. Liu 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.
Kyng, Rasmus, et al.. (2025). Maximum Flow and Minimum-Cost Flow in Almost-Linear Time. Journal of the ACM. 72(3). 1–103.
2.
Lee, James R., et al.. (2024). Sparsifying Generalized Linear Models. 1665–1675.
3.
4.
Liu, Yang P.. (2024). On Approximate Fully-Dynamic Matching and Online Matrix-Vector Multiplication. 228–243. 2 indexed citations
5.
Liu, Yang P., et al.. (2024). Discrepancy Minimization via a Self-Balancing Walk. SIAM Journal on Computing. STOC21–211.
6.
Brand, Jan van den, Yang P. Liu, & Aaron Sidford. (2023). Dynamic Maxflow via Dynamic Interior Point Methods. 1215–1228. 4 indexed citations
7.
Liu, Yang P., et al.. (2023). Chaining, Group Leverage Score Overestimates, and Fast Spectral Hypergraph Sparsification. 196–206. 2 indexed citations
8.
Lee, James R., et al.. (2023). Sparsifying Sums of Norms. 1953–1962. 3 indexed citations
9.
Brand, Jan van den, Li Chen, Rasmus Kyng, et al.. (2023). A Deterministic Almost-Linear Time Algorithm for Minimum-Cost Flow. 503–514. 11 indexed citations
10.
Chen, Li, Rasmus Kyng, Yang P. Liu, et al.. (2023). Almost-Linear-Time Algorithms for Maximum Flow and Minimum-Cost Flow. Communications of the ACM. 66(12). 85–92. 2 indexed citations
11.
Liu, Yang P., et al.. (2022). Unit Capacity Maxflow in Almost $m^{4/3}$ Time. SIAM Journal on Computing. 53(6). FOCS20–175. 4 indexed citations
12.
Chen, Li, Rasmus Kyng, Yang P. Liu, et al.. (2022). Maximum Flow and Minimum-Cost Flow in Almost-Linear Time. 612–623. 59 indexed citations
13.
Liu, Yang P., et al.. (2022). Minor Sparsifiers and the Distributed Laplacian Paradigm. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 989–999. 4 indexed citations
14.
15.
Liu, Yang P., et al.. (2021). Discrepancy minimization via a self-balancing walk. 14–20. 8 indexed citations
16.
Brand, Jan van den, Yin Tat Lee, Yang P. Liu, et al.. (2021). Minimum cost flows, MDPs, and ℓ 1 -regression in nearly linear time for dense instances. 859–869. 23 indexed citations
17.
Alon, Noga, et al.. (2021). Arithmetic Progressions in Sumsets of Sparse Sets. Repository for Publications and Research Data (ETH Zurich).
18.
Liu, Yang P., et al.. (2020). Unit Capacity Maxflow in Almost Time. 119–130. 11 indexed citations
19.
Liu, Yang P. & Yufei Zhao. (2020). On the upper tail problem for random hypergraphs. Random Structures and Algorithms. 58(2). 179–220. 8 indexed citations
20.
Liu, Yang P., et al.. (2019). Parallel Reachability in Almost Linear Work and Square Root Depth. 1664–1686. 7 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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