Qianxiao Li

2.4k total citations · 2 hit papers
56 papers, 1.2k citations indexed

About

Qianxiao Li is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Materials Chemistry. According to data from OpenAlex, Qianxiao Li has authored 56 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Statistical and Nonlinear Physics, 19 papers in Artificial Intelligence and 11 papers in Materials Chemistry. Recurrent topics in Qianxiao Li's work include Model Reduction and Neural Networks (18 papers), Machine Learning in Materials Science (10 papers) and Neural Networks and Applications (8 papers). Qianxiao Li is often cited by papers focused on Model Reduction and Neural Networks (18 papers), Machine Learning in Materials Science (10 papers) and Neural Networks and Applications (8 papers). Qianxiao Li collaborates with scholars based in Singapore, United States and China. Qianxiao Li's co-authors include Felix Dietrich, Ioannis G. Kevrekidis, Erik M. Bollt, Tonio Buonassisi, Kedar Hippalgaonkar, Xiaonan Wang, Jatin Kumar, Jun Ye, Zekun Ren and E Weinan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Advanced Functional Materials and Journal of Computational Physics.

In The Last Decade

Qianxiao Li

53 papers receiving 1.2k citations

Hit Papers

align trajectories

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.

Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator

2017 238 citations Qianxiao Li, Felix Dietrich et al. profile →
Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics

2023 94 citations Kedar Hippalgaonkar, Qianxiao Li et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qianxiao Li Singapore	15	448	299	185	177	176	56	1.2k
Xiu Yang United States	18	94 0.2×	175 0.6×	125 0.7×	106 0.6×	186 1.1×	59	954
Shuai Yang China	22	263 0.6×	398 1.3×	170 0.9×	219 1.2×	134 0.8×	69	1.4k
Lin Xiao China	13	632 1.4×	79 0.3×	116 0.6×	196 1.1×	70 0.4×	37	1.5k
Kaiwen Zhou China	20	287 0.6×	47 0.2×	93 0.5×	148 0.8×	142 0.8×	73	1.1k
Jianying Yang China	20	326 0.7×	180 0.6×	108 0.6×	164 0.9×	145 0.8×	95	1.5k
Dong Ni China	18	144 0.3×	47 0.2×	132 0.7×	250 1.4×	79 0.4×	67	933
Yuki Sato Japan	17	280 0.6×	45 0.2×	108 0.6×	157 0.9×	304 1.7×	114	1.6k
Maria Longobardi Italy	20	302 0.7×	301 1.0×	126 0.7×	196 1.1×	129 0.7×	60	1.5k
Joel A. Paulson United States	25	196 0.4×	82 0.3×	178 1.0×	356 2.0×	117 0.7×	95	1.8k

Countries citing papers authored by Qianxiao Li

Since Specialization

Citations

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

Fields of papers citing papers by Qianxiao Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qianxiao Li

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Guo, Y. P., Milan Korda, Ioannis G. Kevrekidis, & Qianxiao Li. (2025). Learning Parametric Koopman Decompositions for Prediction and Control. SIAM Journal on Applied Dynamical Systems. 24(1). 744–781. 1 indexed citations

Li, Qianxiao, et al.. (2025). Interpolation, Approximation, and Controllability of Deep Neural Networks. SIAM Journal on Control and Optimization. 63(1). 625–649. 3 indexed citations

Mekki‐Berrada, Flore, Abhishek Gupta, Jiaxun Xie, et al.. (2024). Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs. npj Computational Materials. 10(1). 34 indexed citations

Tian, Siyu, Zekun Ren, Selvaraj Venkataraj, et al.. (2024). Correction: Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films. Digital Discovery. 3(5). 1068–1068.

Tian, Siyu, Zekun Ren, Selvaraj Venkataraj, et al.. (2023). Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films. Digital Discovery. 2(5). 1334–1346. 6 indexed citations

Ren, Zekun, et al.. (2023). Fast Bayesian optimization of Needle-in-a-Haystack problems using zooming memory-based initialization (ZoMBI). npj Computational Materials. 9(1). 20 indexed citations

Li, Qianxiao, et al.. (2023). A Brief Survey on the Approximation Theory for Sequence Modelling. 2(1). 1–30. 2 indexed citations

Li, Qianxiao, et al.. (2022). Computing the Invariant Distribution of Randomly Perturbed Dynamical Systems Using Deep Learning. Journal of Scientific Computing. 91(3). 7 indexed citations

Li, Qianxiao, et al.. (2022). Deep learning via dynamical systems: An approximation perspective. Journal of the European Mathematical Society. 25(5). 1671–1709. 31 indexed citations

10.

Li, Qianxiao, et al.. (2022). Computing high-dimensional invariant distributions from noisy data. Journal of Computational Physics. 474. 111783–111783. 6 indexed citations

11.

Li, Qianxiao, et al.. (2021). Towards Robust Neural Networks via Close-loop Control. International Conference on Learning Representations. 4 indexed citations

12.

Mekki‐Berrada, Flore, Zekun Ren, Tan Huang, et al.. (2021). Two-step machine learning enables optimized nanoparticle synthesis. npj Computational Materials. 7(1). 174 indexed citations

13.

Bash, Daniil, Vijila Chellappan, Swee Liang Wong, et al.. (2021). Multi‐Fidelity High‐Throughput Optimization of Electrical Conductivity in P3HT‐CNT Composites. Advanced Functional Materials. 31(36). 34 indexed citations

14.

Ye, Nanyang, Qianxiao Li, Xiao-Yun Zhou, & Zhanxing Zhu. (2021). An Annealing Mechanism for Adversarial Training Acceleration. IEEE Transactions on Neural Networks and Learning Systems. 34(2). 882–893. 7 indexed citations

15.

Ren, Zekun, Felipe Oviedo, Siyu Tian, et al.. (2020). Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics. npj Computational Materials. 6(1). 28 indexed citations

16.

Ren, Zekun, Felipe Oviedo, Siyu Tian, et al.. (2020). Author Correction: Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics. npj Computational Materials. 6(1). 1 indexed citations

17.

Weinan, E, Jiequn Han, & Qianxiao Li. (2019). A Mean-Field Optimal Control Formulation of Deep Learning. National University of Singapore. 1 indexed citations

18.

Li, Qianxiao & Shuji Hao. (2018). An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks. International Conference on Machine Learning. 2985–2994. 4 indexed citations

19.

Dietrich, Felix, Qianxiao Li, Erik M. Bollt, et al.. (2017). An Equal Space for Complex Data with Unknown Internal Order: Observability, Gauge Invariance and Manifold Learning. arXiv (Cornell University). 1 indexed citations

20.

Chazelle, Bernard, Quansen Jiu, Qianxiao Li, & Chu Wang. (2017). Well-posedness of the limiting equation of a noisy consensus model in opinion dynamics. Journal of Differential Equations. 263(1). 365–397. 22 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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