Sumanta Das

2.2k citations
84 papers · 1.7k · 1 hit paper · h-index 23

Impact in

Papers in

Sumanta Das

82 papers receiving 1.7k citations

Hit Papers

Prediction of concrete strengths enabled by missing data imputation and interpretable machine learning 2022 · 154 citations
1540+1+2Years since publication50100150

Peers

Sumanta Das
Comparison fields: 5 of 95
  • Civil and Structural Engineering 1.0k
  • Nuclear Energy and Engineering 15
  • Building and Construction 392
  • Ceramics and Composites 105
  • Mechanical Engineering 476
Replace Yue Li with:
Yue Li China
Luca Sorelli Canada
Nagesh R. Iyer India
Jian Liu China
Tao Shi China
Sukhoon Pyo South Korea
Shangtong Yang United Kingdom
Qiwen Qiu Hong Kong
Sumanta Das relative to Yue Li China Yue Li's profile →
Citations per field
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Countries citing papers authored by Sumanta Das

Since Specialization
Citations

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

Fields of papers citing papers by Sumanta Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sumanta Das, 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 Sumanta Das Line = papers co-authored together Sumanta Das links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Prediction of concrete strengths enabled by missing data imputation and interpretable machine learning
Hit paper breakdown →
2022154
2 2016153
3 2015118
4 201870
5 201768
6 201462
7 201952
8 201443
9 202140
10 201540
11 201938
12 201935
13 201934
14 201634
15 201434
16 202032
17 202131
18 202330
19 201530
20 201530

About Sumanta Das

Sumanta Das is a scholar working on Civil and Structural Engineering, Mechanics of Materials, Mechanical Engineering, Building and Construction and Materials Chemistry, having authored 84 papers that have together received 1.7k indexed citations. Recurring topics across this work include Concrete and Cement Materials Research (22 papers), Innovative concrete reinforcement materials (15 papers), Wood Treatment and Properties (13 papers), Concrete Properties and Behavior (9 papers), Rock Mechanics and Modeling (9 papers), Smart Materials for Construction (8 papers), Phase Change Materials Research (7 papers) and Composite Material Mechanics (6 papers). The work is most often cited by research in Civil and Structural Engineering (1.0k citations), Nuclear Energy and Engineering (15 citations), Building and Construction (392 citations), Ceramics and Composites (105 citations) and Mechanical Engineering (476 citations). Sumanta Das has collaborated with scholars based in United States, India and Czechia. Frequent co-authors include Narayanan Neithalath, N. M. Anoop Krishnan, Gideon A. Lyngdoh, Gaurav Sant, Matthew Aguayo, Mohd Zaki, Nikhilesh Chawla, James C.E. Mertens, David Stone and Nihat Kabay. Their work appears in journals such as Construction and Building Materials, Cement and Concrete Composites, Materials & Design, Journal of Building Engineering and Materials.

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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