Khemraj Shukla
- Statistical and Nonlinear Physics top 2%
- Geophysics top 5%
- Artificial Intelligence top 10%
- Computational Mechanics top 5%
- Mechanics of Materials top 10%
- Co-authors
- George Em KarniadakisChristian HuberVivek OommenRémi DingrevilleSomdatta GoswamiKenji KawaguchiZheyuan HuAmeya D. Jagtap
- Topics
- Seismic Waves and Analysis (13 papers)Seismic Imaging and Inversion Techniques (12 papers)Model Reduction and Neural Networks (10 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Fluid MechanicsJournal of Computational Physics
- Partner nations
- United StatesItalySpain
In The Last Decade
Khemraj Shukla
31 papers receiving 860 citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Statistical and Nonlinear Physics 352
- Geophysics 257
- Artificial Intelligence 184
- Computational Mechanics 153
- Mechanics of Materials 116
Countries citing papers authored by Khemraj Shukla
This map shows the geographic impact of Khemraj Shukla'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 Khemraj Shukla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khemraj Shukla more than expected).
Fields of papers citing papers by Khemraj Shukla
This network shows the impact of papers produced by Khemraj Shukla. 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 Khemraj Shukla. The network helps show where Khemraj Shukla may publish in the future.
Co-authorship network of co-authors of Khemraj Shukla
This figure shows the co-authorship network connecting the top 25 collaborators of Khemraj Shukla. A scholar is included among the top collaborators of Khemraj Shukla 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 Khemraj Shukla. Khemraj Shukla is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 21 | |
| 6 | 25 | |
| 7 | Tackling the curse of dimensionality with physics-informed neural networksbreakdown → | 72 |
| 8 | 9 | |
| 9 | 16 | |
| 10 | 2 | |
| 11 | 17 | |
| 12 | 101 | |
| 13 | Physics‐Informed Neural Networks (PINNs) for Wave Propagation and Full Waveform Inversionsbreakdown → | 234 |
| 14 | 15 | |
| 15 | 10 | |
| 16 | 3 | |
| 17 | 3 | |
| 18 | 1 | |
| 19 | 2 | |
| 20 | 21 |
About Khemraj Shukla
Khemraj Shukla is a scholar working on Geophysics, Statistical and Nonlinear Physics and Structural Biology, having authored 33 papers that have together received 892 indexed citations. Recurring topics across this work include Seismic Waves and Analysis (13 papers), Seismic Imaging and Inversion Techniques (12 papers) and Model Reduction and Neural Networks (10 papers). The work is most often cited by research in Statistical and Nonlinear Physics (352 citations), Geophysics (257 citations) and Computational Mechanics (153 citations). Khemraj Shukla has collaborated with scholars based in United States, Italy and Spain. Frequent co-authors include George Em Karniadakis, Christian Huber, Vivek Oommen, Rémi Dingreville, Somdatta Goswami, Kenji Kawaguchi, Zheyuan Hu, Ameya D. Jagtap, James L. Blackshire and Sankar Kumar Nath. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Fluid Mechanics and Journal of Computational Physics.
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.