Ehsan Kharazmi

2.4k citations
15 papers · 1.5k · 2 hit papers · h-index 10

Impact in

Papers in

Ehsan Kharazmi

15 papers receiving 1.5k citations

Ehsan Kharazmi's Hit Papers

hp-VPINNs: Variational physics-informed neural networks with domain decomposition 2020 · 508 citations
5080+2+4Years since publication200400600

Peers

Ehsan Kharazmi
Comparison fields: 5 of 82
  • Statistical and Nonlinear Physics 1.1k
  • Modeling and Simulation 180
  • Computational Mechanics 474
  • Statistics, Probability and Uncertainty 140
  • Numerical Analysis 91
Replace Bing Yu with:
Bing Yu China
Yibo Yang United States
Liang Yan China
Anindya Chatterjee India
Hanwen Wang China
Minglang Yin United States
Han Gao United States
Jens Berg Sweden
Suchuan Dong United States
John Burkardt United States
Ehsan Kharazmi relative to Bing Yu China Bing Yu's profile →
Citations per field
00.5×3.7×
Bing Yu · 1×
Citations per year

Countries citing papers authored by Ehsan Kharazmi

Since Specialization
Citations

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

Fields of papers citing papers by Ehsan Kharazmi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Ehsan Kharazmi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ehsan Kharazmi Line = papers co-authored together Ehsan Kharazmi links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems
Hit paper breakdown →
2020741
2
hp-VPINNs: Variational physics-informed neural networks with domain decomposition
Hit paper breakdown →
2020508
3 202190
4 201735
5 201832
6 202122
7 202117
8 201914
9 202011
10 202111
11 20226
12 20156
13 20195
14 20223
15 20251

About Ehsan Kharazmi

Ehsan Kharazmi is a scholar working on Modeling and Simulation, Computational Mechanics, Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty and Numerical Analysis, having authored 15 papers that have together received 1.5k indexed citations. Recurring topics across this work include Fractional Differential Equations Solutions (7 papers), Model Reduction and Neural Networks (5 papers), Probabilistic and Robust Engineering Design (4 papers), Fluid Dynamics and Turbulent Flows (4 papers), Fluid Dynamics and Vibration Analysis (4 papers), Numerical methods in engineering (3 papers), Differential Equations and Numerical Methods (3 papers) and Wind and Air Flow Studies (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.1k citations), Modeling and Simulation (180 citations), Computational Mechanics (474 citations), Statistics, Probability and Uncertainty (140 citations) and Numerical Analysis (91 citations). Ehsan Kharazmi has collaborated with scholars based in United States and China. Frequent co-authors include George Em Karniadakis, Ameya D. Jagtap, Zhongqiang Zhang, Mohsen Zayernouri, Min Cai, Xiaoning Zheng, Zhen Zhang, Guang Lin, Dixia Fan and Michael S. Triantafyllou. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, Journal of Fluids and Structures, Nature Computational Science, Journal of Sound and Vibration and Nonlinear Dynamics.

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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