Ji Liu

3.2k total citations
45 papers, 654 citations indexed

About

Ji Liu is a scholar working on Artificial Intelligence, Computational Mechanics and Computational Theory and Mathematics. According to data from OpenAlex, Ji Liu has authored 45 papers receiving a total of 654 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 9 papers in Computational Mechanics and 9 papers in Computational Theory and Mathematics. Recurrent topics in Ji Liu's work include Quantum Computing Algorithms and Architecture (22 papers), Quantum Information and Cryptography (17 papers) and Stochastic Gradient Optimization Techniques (10 papers). Ji Liu is often cited by papers focused on Quantum Computing Algorithms and Architecture (22 papers), Quantum Information and Cryptography (17 papers) and Stochastic Gradient Optimization Techniques (10 papers). Ji Liu collaborates with scholars based in United States, China and Australia. Ji Liu's co-authors include Stephen J. Wright, Huiyang Zhou, Xiangru Lian, Yijun Huang, Yuncheng Li, Christopher Ré, Victor Bittorf, Steve Wright, Tong Zhang and Jianqiao Wangni and has published in prestigious journals such as Nature Communications, Nature Structural & Molecular Biology and Mathematics of Computation.

In The Last Decade

Ji Liu

36 papers receiving 625 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ji Liu United States 12 538 196 110 91 88 45 654
François Le Gall Japan 8 317 0.6× 36 0.2× 105 1.0× 62 0.7× 55 0.6× 35 573
Jelani Nelson United States 14 540 1.0× 237 1.2× 266 2.4× 38 0.4× 137 1.6× 38 854
Berkant Savas Sweden 10 140 0.3× 151 0.8× 38 0.3× 20 0.2× 85 1.0× 19 531
Ioannis Koutis United States 14 159 0.3× 61 0.3× 113 1.0× 73 0.8× 125 1.4× 41 569
Aaron Sidford United States 12 231 0.4× 111 0.6× 129 1.2× 31 0.3× 41 0.5× 37 546
Pedro M. Crespo Spain 17 250 0.5× 96 0.5× 416 3.8× 525 5.8× 90 1.0× 101 926
Matus Telgarsky United States 7 223 0.4× 121 0.6× 25 0.2× 22 0.2× 54 0.6× 15 469
Hamed Hassani United States 12 355 0.7× 55 0.3× 303 2.8× 180 2.0× 64 0.7× 54 629
Luis Rademacher United States 7 193 0.4× 180 0.9× 45 0.4× 36 0.4× 98 1.1× 26 401
C.-T. Pan United States 9 95 0.2× 123 0.6× 56 0.5× 57 0.6× 31 0.4× 14 410

Countries citing papers authored by Ji Liu

Since Specialization
Citations

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

Fields of papers citing papers by Ji Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ji Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Ji Liu. A scholar is included among the top collaborators of Ji 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 Ji Liu. Ji 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.
Campbell, Colin, et al.. (2025). Efficient sparse state preparation via quantum walks. npj Quantum Information. 11(1).
2.
Hovland, Paul, et al.. (2025). Is Circuit Depth Accurate for Comparing Quantum Circuit Runtimes?. 368–374.
3.
Zhang, Shengchun, Ran Yi, Li An, et al.. (2025). Structural insights into higher-order natural RNA-only multimers. Nature Structural & Molecular Biology. 32(10). 2012–2021. 1 indexed citations
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Campbell, Colin, et al.. (2024). Arbitrary State Preparation via Quantum Walks. 616–617.
7.
Liu, Ji, Ruoming Jin, Zijie Zhang, et al.. (2024). Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models. 10497–10523. 2 indexed citations
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11.
Liu, Ji, et al.. (2023). Tackling the Qubit Mapping Problem with Permutation-Aware Synthesis. 745–756. 9 indexed citations
12.
Liu, Ji, et al.. (2021). Stochastically Controlled Compositional Gradient for Composition Problems. IEEE Transactions on Neural Networks and Learning Systems. 34(2). 611–622. 2 indexed citations
13.
Zhou, Xichuan, Kui Liu, Cong Shi, Haijun Liu, & Ji Liu. (2021). Optimizing Information Theory Based Bitwise Bottlenecks for Efficient Mixed-Precision Activation Quantization. Proceedings of the AAAI Conference on Artificial Intelligence. 35(4). 3590–3598. 2 indexed citations
14.
Liu, Ji & Huiyang Zhou. (2020). Reliability Modeling of NISQ- Era Quantum Computers. 94–105. 25 indexed citations
15.
Yang, Haichuan, et al.. (2019). Learning Sparsity and Quantization Jointly and Automatically for Neural Network Compression via Constrained Optimization.. arXiv (Cornell University). 3 indexed citations
16.
Zhang, Tong, et al.. (2018). Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 31. 8366–8375. 7 indexed citations
17.
Wangni, Jianqiao, Jialei Wang, Ji Liu, & Tong Zhang. (2018). Gradient Sparsification for Communication-Efficient Distributed Optimization. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 31. 1299–1309. 63 indexed citations
18.
Wang, Mengdi, Ji Liu, & Ethan X. Fang. (2016). Accelerating Stochastic Composition Optimization. Journal of Machine Learning Research. 18(105). 1–1730. 2 indexed citations
19.
Lian, Xiangru, Yijun Huang, Yuncheng Li, & Ji Liu. (2015). Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization. arXiv (Cornell University). 107 indexed citations
20.
Liu, Ji, et al.. (2013). An Asynchronous Parallel Stochastic Coordinate Descent Algorithm. Journal of Machine Learning Research. 16(1). 285–322. 94 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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