Lu Lu
Impact in
- Statistical and Nonlinear Physics top 0.01%
- Model Reduction and Neural Networks
- Nonlinear Waves and Solitons
- Modeling and Simulation top 1%
- Fractional Differential Equations Solutions
Papers in
-
- Model Reduction and Neural Networks 53
- Genetics 4
- Hemoglobinopathies and Related Disorders 4
- Co-authors
- George Em Karniadakis (29 shared papers)Paris G. Perdikaris (4 shared papers)Sifan Wang (5 shared papers)Yannis Kevrekidis (1 shared paper)Liu Yang (1 shared paper)Xuhui Meng (3 shared papers)Zhiping Mao (3 shared papers)Guofei Pang (1 shared paper)
- Journals
- Journal of Computational Physics (7 papers)Computer Methods in Applied Mechanics and Engineering (7 papers)Biophysical Journal (4 papers)SIAM Journal on Scientific Computing (4 papers)PLoS Computational Biology (3 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Lu Lu
73 papers receiving 14.4k citations
Lu Lu's Hit Papers
Peers
Comparison fields: 5 of 168
- Statistical and Nonlinear Physics 9k
- Modeling and Simulation 284
- Artificial Intelligence 954
- Environmental Engineering 337
- Automotive Engineering 231
Countries citing papers authored by Lu Lu
This map shows the geographic impact of Lu Lu'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 Lu Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lu Lu more than expected).
Fields of papers citing papers by Lu Lu
This network shows the impact of papers produced by Lu Lu. 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 Lu Lu. The network helps show where Lu Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Lu Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Physics-informed machine learning Hit paper breakdown → | 2021 | 5121 |
| 2 | Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators Hit paper breakdown → | 2021 | 2043 |
| 3 | DeepXDE: A Deep Learning Library for Solving Differential Equations Hit paper breakdown → | 2021 | 1685 |
| 4 | fPINNs: Fractional Physics-Informed Neural Networks Hit paper breakdown → | 2019 | 784 |
| 5 | Physics-Informed Neural Networks with Hard Constraints for Inverse Design Hit paper breakdown → | 2021 | 550 |
| 6 | Physics-informed neural networks for inverse problems in nano-optics and metamaterials Hit paper breakdown → | 2020 | 546 |
| 7 | Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Hit paper breakdown → | 2022 | 510 |
| 8 | A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Hit paper breakdown → | 2022 | 458 |
| 9 | Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems Hit paper breakdown → | 2019 | 377 |
| 10 | Extraction of mechanical properties of materials through deep learning from instrumented indentation Hit paper breakdown → | 2020 | 276 |
| 11 | 2020 | 244 | |
| 12 | 2020 | 208 | |
| 13 | DeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks Hit paper breakdown → | 2021 | 179 |
| 14 | MIONet: Learning Multiple-Input Operators via Tensor Product Hit paper breakdown → | 2022 | 156 |
| 15 | 2021 | 130 | |
| 16 | 2022 | 127 | |
| 17 | 2021 | 121 | |
| 18 | 2018 | 113 | |
| 19 | 2021 | 103 | |
| 20 | Reliable Extrapolation of Deep Neural Operators Informed by Physics or Sparse Observations Hit paper breakdown → | 2023 | 103 |
About Lu Lu
Lu Lu is a scholar working on Statistical and Nonlinear Physics, Genetics, Physiology, Artificial Intelligence and Pulmonary and Respiratory Medicine, having authored 80 papers that have together received 14.8k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (53 papers), Blood properties and coagulation (5 papers), Erythrocyte Function and Pathophysiology (4 papers), Hemoglobinopathies and Related Disorders (4 papers), Lipid Membrane Structure and Behavior (3 papers), Control Systems and Identification (3 papers), Elasticity and Material Modeling (2 papers) and Computational Fluid Dynamics and Aerodynamics (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (9k citations), Modeling and Simulation (284 citations), Artificial Intelligence (954 citations), Environmental Engineering (337 citations) and Automotive Engineering (231 citations). Lu Lu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include George Em Karniadakis, Paris G. Perdikaris, Sifan Wang, Yannis Kevrekidis, Liu Yang, Xuhui Meng, Zhiping Mao, Guofei Pang, Min Zhu and Luca Dal Negro. Their work appears in journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering, Biophysical Journal, SIAM Journal on Scientific Computing and PLoS Computational Biology.
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.