Somdatta Goswami

3.8k citations
34 papers · 2.6k indexed · 3 hit papers · h-index 18
Topics
Model Reduction and Neural Networks (17 papers)Numerical methods in engineering (8 papers)Probabilistic and Robust Engineering Design (7 papers)

In The Last Decade

Somdatta Goswami

29 papers receiving 2.5k citations

Hit Papers

An energy approach to the solution of partial differentia...20202026202220242020202220244008001.2k

Peers

Somdatta Goswami
Comparison fields: 5 of 108
  • Mechanics of Materials 1.0k
  • Statistical and Nonlinear Physics 733
  • Civil and Structural Engineering 732
  • Mechanical Engineering 481
  • Computational Mechanics 478
Replace Khader M. Hamdia with:
Khader M. Hamdia Germany
Ehsan Haghighat United States
Hongwei Guo China
WaiChing Sun United States
Pierre Kerfriden United Kingdom
Cosmin Anitescu Germany
Seid Korić United States
Stefano Mariani Italy
Genki YAGAWA Japan
Somdatta Goswami relative to Khader M. Hamdia Germany Khader M. Hamdia's profile →
Citations per field
00.5×2.6×
Khader M. Hamdia · 1×
Citations per year

Countries citing papers authored by Somdatta Goswami

Since Specialization
Citations

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

Fields of papers citing papers by Somdatta Goswami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Somdatta Goswami

This figure shows the co-authorship network connecting the top 25 collaborators of Somdatta Goswami. A scholar is included among the top collaborators of Somdatta Goswami 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 Somdatta Goswami. Somdatta Goswami 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
#WorkIndexed citations
1 2
2 0
3 4
4 0
5 0
6 0
7 0
8 16
9 8
10 31
11 12
12 2
13 28
14 33
15 31
16 7
17 101
18 21
19
A physics-informed variational DeepONet for predicting crack path in quasi-brittle materialsbreakdown →
249
20
An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applicationsbreakdown →
1392

About Somdatta Goswami

Somdatta Goswami is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty and Computational Mechanics, having authored 34 papers that have together received 2.6k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (17 papers), Numerical methods in engineering (8 papers) and Probabilistic and Robust Engineering Design (7 papers). The work is most often cited by research in Statistical and Nonlinear Physics (733 citations), Statistics, Probability and Uncertainty (304 citations) and Mechanics of Materials (1.0k citations). Somdatta Goswami has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Cosmin Anitescu, Timon Rabczuk, Khader M. Hamdia, Esteban Samaniego, Hongwei Guo, Xiaoying Zhuang, George Em Karniadakis, Yue Yu, Minglang Yin and Subrata Chakraborty. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Scientific Reports.

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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