Swati Dey

553 total citations
23 papers, 420 citations indexed

About

Swati Dey is a scholar working on Mechanical Engineering, Mechanics of Materials and Aerospace Engineering. According to data from OpenAlex, Swati Dey has authored 23 papers receiving a total of 420 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Mechanical Engineering, 10 papers in Mechanics of Materials and 7 papers in Aerospace Engineering. Recurrent topics in Swati Dey's work include Aluminum Alloy Microstructure Properties (7 papers), Metallurgy and Material Forming (6 papers) and Orthopaedic implants and arthroplasty (5 papers). Swati Dey is often cited by papers focused on Aluminum Alloy Microstructure Properties (7 papers), Metallurgy and Material Forming (6 papers) and Orthopaedic implants and arthroplasty (5 papers). Swati Dey collaborates with scholars based in India, Nepal and United States. Swati Dey's co-authors include Shubhabrata Datta, Debdulal Das, Partha Pratim Dey, Dev S. Pathak, Sandipan Roy, Shubrajit Bhaumik, Niloy Khutia, Amit Roy Chowdhury, Subrata Chatterjee and Santanu Pattanayak and has published in prestigious journals such as Journal of the American College of Cardiology, Journal of Alloys and Compounds and Composite Structures.

In The Last Decade

Swati Dey

23 papers receiving 413 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Swati Dey India 12 247 140 114 67 61 23 420
E.C. Santos Japan 11 408 1.7× 146 1.0× 122 1.1× 62 0.9× 14 0.2× 20 510
Rıza Gürbüz Türkiye 10 210 0.9× 52 0.4× 60 0.5× 61 0.9× 24 0.4× 35 384
V. V. Kulyk Ukraine 16 349 1.4× 173 1.2× 354 3.1× 38 0.6× 8 0.1× 67 577
Maria Clara Filippini Ierardi Brazil 9 350 1.4× 65 0.5× 193 1.7× 72 1.1× 12 0.2× 15 451
J. Pinho-da-Cruz Portugal 9 296 1.2× 314 2.2× 104 0.9× 70 1.0× 7 0.1× 23 551
Héctor Javier Vergara–Hernández Mexico 12 295 1.2× 67 0.5× 216 1.9× 65 1.0× 42 0.7× 78 423
Yifei Zhang China 11 278 1.1× 50 0.4× 98 0.9× 69 1.0× 14 0.2× 24 345
Alexander Tyurin Russia 10 101 0.4× 55 0.4× 157 1.4× 123 1.8× 39 0.6× 36 278
H. Pohl Germany 7 670 2.7× 51 0.4× 97 0.9× 76 1.1× 14 0.2× 11 747
Hong Zhao China 12 386 1.6× 100 0.7× 282 2.5× 37 0.6× 4 0.1× 60 601

Countries citing papers authored by Swati Dey

Since Specialization
Citations

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

Fields of papers citing papers by Swati Dey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Swati Dey

This figure shows the co-authorship network connecting the top 25 collaborators of Swati Dey. A scholar is included among the top collaborators of Swati Dey 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 Swati Dey. Swati Dey 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
1.
Dey, Swati, Benjamin Vaughan, Grace Chen, et al.. (2022). THE CINCINNATI ATRIAL FIBRILLATION SCORE (CAFS): MULTICENTER VALIDATION OF THE FIRST POLYSOMNOGRAPHY-BASED RISK SCORE FOR PREDICTING INCIDENT ATRIAL FIBRILLATION IN ASYMPTOMATIC AMBULATORY COMMUNITY ADULTS. Journal of the American College of Cardiology. 79(9). 27–27. 1 indexed citations
2.
Khutia, Niloy, et al.. (2022). Influence of Carbon Nanotube Defects on the Elastic Modulus of Nanocomposite: Multiscale Simulation. Journal of Materials Engineering and Performance. 32(5). 2356–2369. 1 indexed citations
3.
Dey, Swati, et al.. (2021). Designing optimized ternary catalytic alloy electrode for efficiency improvement of semiconductor gas sensors using a machine learning approach. Decision Making Applications in Management and Engineering. 4(2). 126–139. 14 indexed citations
4.
Dey, Swati, et al.. (2020). Design of Ti composite with bioactive surface for dental implant. Materials and Manufacturing Processes. 35(6). 643–651. 14 indexed citations
5.
Dey, Swati, et al.. (2020). Design of Alumina Reinforced Aluminium Alloy Composites with Improved Tribo-Mechanical Properties: A Machine Learning Approach. Transactions of the Indian Institute of Metals. 73(12). 3059–3069. 28 indexed citations
6.
Dey, Swati, et al.. (2020). Modelling of tribological responses of composites using integrated ANN-GA technique. Journal of Composite Materials. 55(7). 873–896. 22 indexed citations
7.
Nandy, Supriya, et al.. (2020). Multi-Objective Genetic Algorithm Based Optimization of Age Hardening for AA6063 Alloy. IOP Conference Series Materials Science and Engineering. 912(5). 52019–52019. 3 indexed citations
8.
Dey, Swati, et al.. (2019). Computational intelligence based design of implant for varying bone conditions. International Journal for Numerical Methods in Biomedical Engineering. 35(6). e3191–e3191. 10 indexed citations
9.
Bhaumik, Shubrajit, Dev S. Pathak, Swati Dey, & Shubhabrata Datta. (2019). Artificial intelligence based design of multiple friction modifiers dispersed castor oil and evaluating its tribological properties. Tribology International. 140. 105813–105813. 52 indexed citations
10.
Dey, Swati, et al.. (2019). Data-driven design of ternary alloy catalysts for enhanced oxide-based gas sensors’ performance. Computational Materials Science. 161. 255–260. 6 indexed citations
11.
Roy, Sandipan, Swati Dey, Niloy Khutia, Amit Roy Chowdhury, & Shubhabrata Datta. (2018). Design of patient specific dental implant using FE analysis and computational intelligence techniques. Applied Soft Computing. 65. 272–279. 65 indexed citations
12.
Biswas, Jayanta Kumar, Swati Dey, Santanu Kumar Karmakar, Amit Roychowdhury, & Shubhabrata Datta. (2018). Design of Patient Specific Spinal Implant (Pedicle Screw Fixation) using FE Analysis and Soft Computing Techniques. Current Medical Imaging Formerly Current Medical Imaging Reviews. 16(4). 371–382. 10 indexed citations
13.
Dey, Swati, et al.. (2018). Designing dual-phase steels with improved performance using ANN and GA in tandem. Computational Materials Science. 157. 6–16. 48 indexed citations
14.
Dey, Swati, et al.. (2018). Intelligent design optimization of age-hardenable Al alloys. Computational Materials Science. 153. 315–325. 8 indexed citations
15.
Dey, Swati, Partha Pratim Dey, & Shubhabrata Datta. (2017). Design of novel age-hardenable aluminium alloy using evolutionary computation. Journal of Alloys and Compounds. 704. 373–381. 24 indexed citations
16.
Dey, Swati, et al.. (2015). Computational intelligence based design of age-hardenable aluminium alloys for different temperature regimes. Materials & Design. 92. 522–534. 34 indexed citations
17.
Pattanayak, Santanu, Swati Dey, Subrata Chatterjee, Sandip Ghosh Chowdhury, & Shubhabrata Datta. (2015). Computational intelligence based designing of microalloyed pipeline steel. Computational Materials Science. 104. 60–68. 36 indexed citations
18.
Tarafder, S., et al.. (2006). Modelling of Crack-tip Blunting using Finite Element Method (FEM) (GAP-0088). 2 indexed citations
19.
Dey, Swati, et al.. (2005). Stretch-zone analysis by image processing for the evaluation of initiation fracture toughness of a HSLA steel. Zeitschrift für Metallkunde. 96(8). 924–932. 2 indexed citations
20.
Dey, Swati, et al.. (2004). Initiation fracture toughness of HSLA steel through automatic measurement of stretch zone. Materials Science and Technology. 20(12). 1531–1537. 13 indexed citations

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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