Abhishek Das

686 total citations
40 papers, 472 citations indexed

About

Abhishek Das is a scholar working on Safety, Risk, Reliability and Quality, Building and Construction and Artificial Intelligence. According to data from OpenAlex, Abhishek Das has authored 40 papers receiving a total of 472 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Safety, Risk, Reliability and Quality, 11 papers in Building and Construction and 10 papers in Artificial Intelligence. Recurrent topics in Abhishek Das's work include Traffic and Road Safety (13 papers), Traffic Prediction and Management Techniques (11 papers) and Traffic control and management (5 papers). Abhishek Das is often cited by papers focused on Traffic and Road Safety (13 papers), Traffic Prediction and Management Techniques (11 papers) and Traffic control and management (5 papers). Abhishek Das collaborates with scholars based in India, United States and Australia. Abhishek Das's co-authors include Mohamed Abdel‐Aty, Anurag Pande, Willem Jan Knibbe, Avijit Kar, Hany M. Hassan, Essam Radwan, Vinayak Dixit, Peter T. Savolainen, Timothy J. Gates and Debashis De and has published in prestigious journals such as IEEE Access, Molecular Pharmacology and Accident Analysis & Prevention.

In The Last Decade

Abhishek Das

37 papers receiving 448 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Abhishek Das India 10 303 191 108 87 64 40 472
Valerian Kwigizile United States 13 359 1.2× 184 1.0× 263 2.4× 104 1.2× 95 1.5× 81 622
Nedal T. Ratrout Saudi Arabia 15 189 0.6× 258 1.4× 254 2.4× 225 2.6× 39 0.6× 47 599
Nopadon Kronprasert Thailand 13 161 0.5× 90 0.5× 147 1.4× 112 1.3× 39 0.6× 41 416
Yichuan Peng China 14 390 1.3× 163 0.9× 178 1.6× 113 1.3× 74 1.2× 36 600
Doohee Nam South Korea 8 352 1.2× 258 1.4× 265 2.5× 110 1.3× 44 0.7× 43 587
Cristian Arteaga United States 10 106 0.3× 128 0.7× 86 0.8× 76 0.9× 22 0.3× 37 414
Xudong Jia United States 12 204 0.7× 138 0.7× 241 2.2× 83 1.0× 49 0.8× 69 549
Randa Oqab Mujalli Jordan 9 537 1.8× 375 2.0× 192 1.8× 49 0.6× 138 2.2× 20 715
João Lourenço Cardoso Portugal 12 205 0.7× 65 0.3× 92 0.9× 40 0.5× 71 1.1× 28 375

Countries citing papers authored by Abhishek Das

Since Specialization
Citations

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

Fields of papers citing papers by Abhishek Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abhishek Das

This figure shows the co-authorship network connecting the top 25 collaborators of Abhishek Das. A scholar is included among the top collaborators of Abhishek Das 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 Abhishek Das. Abhishek Das 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.
De, Debashis, et al.. (2024). MKFF: mid-point K-means based clustering in wireless sensor network for forest fire prediction. Microsystem Technologies. 30(4). 469–480. 5 indexed citations
2.
Das, Abhishek, et al.. (2023). AndyWar: an intelligent android malware detection using machine learning. Innovations in Systems and Software Engineering. 21(1). 303–311. 5 indexed citations
3.
Das, Abhishek, et al.. (2023). Quality aware cost efficient reward mechanism in mobile crowdsensing system with uncertainty constraints. Microsystem Technologies. 30(4). 381–390. 2 indexed citations
4.
Das, Abhishek, et al.. (2019). Deep Learning based Integrated Stacked Model for the Stock Market Prediction. International Journal of Engineering and Advanced Technology. 9(1). 5167–5174. 10 indexed citations
5.
Das, Abhishek, et al.. (2014). Early Detection of Cervical Cancer Using Novel Segmentation Algorithms. 7(2). 91–95. 6 indexed citations
6.
Das, Abhishek, et al.. (2013). Probabilistic Segmentation Methods for Early Detection of Uterine Cervical Cancer. 1(1). 28–31. 1 indexed citations
7.
Savolainen, Peter T., Abhishek Das, Timothy J. Gates, & Tapan K Datta. (2011). Cell Phone Use and Crash Patterns Among Michigan Drivers. Transportation Research Board 90th Annual MeetingTransportation Research Board. 2 indexed citations
8.
Pande, Anurag, Abhishek Das, Mohamed Abdel‐Aty, & Hany M. Hassan. (2011). Real-Time Crash Risk Estimation: Are All Freeways Created Equal?. Veterinary Research Communications. 10(6). 463–7. 21 indexed citations
9.
Das, Abhishek & Mohamed Abdel‐Aty. (2011). A combined frequency–severity approach for the analysis of rear-end crashes on urban arterials. Safety Science. 49(8-9). 1156–1163. 46 indexed citations
10.
Dixit, Vinayak, Anurag Pande, Mohamed Abdel‐Aty, Abhishek Das, & Essam Radwan. (2011). Quality of traffic flow on urban arterial streets and its relationship with safety. Accident Analysis & Prevention. 43(5). 1610–1616. 25 indexed citations
11.
Das, Abhishek, Mohamed Abdel‐Aty, & Anurag Pande. (2010). Genetic Programming to Investigate Design Parameters Contributing to Crash Occurrence on Urban Arterials. Transportation Research Record Journal of the Transportation Research Board. 2147(1). 25–32. 6 indexed citations
12.
Pande, Anurag, Mohamed Abdel‐Aty, & Abhishek Das. (2010). A classification tree based modeling approach for segment related crashes on multilane highways. Journal of Safety Research. 41(5). 391–397. 38 indexed citations
13.
Dixit, Vinayak, Anurag Pande, Mohamed Abdel‐Aty, Essam Radwan, & Abhishek Das. (2009). Relationship of Two-Fluid Model Parameters with Safety on Arterials. DigitalCommons - CalPoly (California State Polytechnic University). 1 indexed citations
14.
Das, Abhishek, et al.. (2009). Severity Analysis of Crashes on Multilane Arterials Using Conditional Inference Forests. Transportation Research Board 88th Annual MeetingTransportation Research Board. 4 indexed citations
15.
Das, Abhishek, Mohamed Abdel‐Aty, & Anurag Pande. (2009). Using conditional inference forests to identify the factors affecting crash severity on arterial corridors. Journal of Safety Research. 40(4). 317–327. 92 indexed citations
16.
Das, Abhishek & Mohamed Abdel‐Aty. (2009). A genetic programming approach to explore the crash severity on multi-lane roads. Accident Analysis & Prevention. 42(2). 548–557. 33 indexed citations
17.
Abdel‐Aty, Mohamed, et al.. (2008). Exploration of Crash Prone Traffic Conditions on Freeways in the Netherlands Using Random Forests. Molecular Pharmacology. 50(6). 1559–66. 1 indexed citations
18.
Abdel‐Aty, Mohamed, Anurag Pande, Abhishek Das, & Willem Jan Knibbe. (2008). Assessing Safety on Dutch Freeways with Data from Infrastructure-Based Intelligent Transportation Systems. Transportation Research Record Journal of the Transportation Research Board. 2083(1). 153–161. 68 indexed citations
19.
Maji, Avijit & Abhishek Das. (2005). Concepts of reliability in mechanistic-empirical bituminous pavement design. 12(1). 1 indexed citations
20.
Das, Abhishek. (2004). Some suggestions to improve the mechanistic-empirical bituminous pavement design in Indian context. 1 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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