Ankit Shah

411 total citations
25 papers, 131 citations indexed

About

Ankit Shah is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Ankit Shah has authored 25 papers receiving a total of 131 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 6 papers in Information Systems. Recurrent topics in Ankit Shah's work include Cloud Computing and Resource Management (4 papers), Distributed and Parallel Computing Systems (4 papers) and IoT and Edge/Fog Computing (3 papers). Ankit Shah is often cited by papers focused on Cloud Computing and Resource Management (4 papers), Distributed and Parallel Computing Systems (4 papers) and IoT and Edge/Fog Computing (3 papers). Ankit Shah collaborates with scholars based in India, United States and Norway. Ankit Shah's co-authors include Kinjal Adhvaryu, Satyajit D. Sarker, M. Mukhlesur Rahman, Ziyi Yang, Poonam Singh Nee Nigam, Lutfun Nahar, Stefanie Tellex, Vasu Sharma, Jeffrey M. Girard and Louis–Philippe Morency and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Allergy and Clinical Immunology and American Journal of Obstetrics and Gynecology.

In The Last Decade

Ankit Shah

20 papers receiving 118 citations

Peers

Ankit Shah
Ankit Shah
Citations per year, relative to Ankit Shah Ankit Shah (= 1×) peers Arvind Panwar

Countries citing papers authored by Ankit Shah

Since Specialization
Citations

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

Fields of papers citing papers by Ankit Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ankit Shah

This figure shows the co-authorship network connecting the top 25 collaborators of Ankit Shah. A scholar is included among the top collaborators of Ankit Shah 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 Ankit Shah. Ankit Shah 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.
Shah, Ankit, et al.. (2024). Skill Transfer for Temporal Task Specification. 2535–2541. 1 indexed citations
2.
Yang, Ziyi, et al.. (2024). Plug in the Safety Chip: Enforcing Constraints for LLM-driven Robot Agents. 14435–14442. 11 indexed citations
4.
Nguyen, Bianca, et al.. (2024). 264 BhCG decline following intrasac methotrexate for the management of cesarean-scar ectopic pregnancy: An 11-year experience.. American Journal of Obstetrics and Gynecology. 230(1). S154–S154. 1 indexed citations
5.
Patel, Mehul & Ankit Shah. (2024). Feature Importance in Machine Learning with Explainable Artificial Intelligence (XAI) for Rainfall Prediction. SHILAP Revista de lepidopterología. 65. 3007–3007. 1 indexed citations
6.
7.
Kheur, Supriya, et al.. (2023). Nipping Leukoplakia in the bud – Brief overview of practice guidelines. SHILAP Revista de lepidopterología. 6. 100023–100023.
10.
Shah, Ankit, et al.. (2020). Intelligent Cricket Team Selection by Predicting Individual Players’ Performance using Efficient Machine Learning Technique. International Journal of Engineering and Advanced Technology. 9(3). 3406–3409. 13 indexed citations
11.
Shah, Ankit, et al.. (2020). Saksham: Resource Aware Block Rearrangement Algorithm for Load Balancing in Hadoop. Procedia Computer Science. 167. 47–56. 4 indexed citations
12.
Shah, Ankit, et al.. (2019). Apache Hadoop A Guide for Cluster Configuration and Testing. International Journal of Computer Sciences and Engineering. 7(4). 792–796. 1 indexed citations
13.
Shah, Ankit, et al.. (2019). Multimodal Behavioral Markers Exploring Suicidal Intent in Social Media Videos. 409–413. 12 indexed citations
15.
Shah, Ankit, et al.. (2018). Load Balancing through Block Rearrangement Policy for Hadoop Heterogeneous Cluster. 230–236. 11 indexed citations
16.
Shah, Ankit. (2012). Antibacterial activities of commonly used traditional Chinese medicines as cold and flu remedies. Journal of Medicinal Plants Research. 6(2). 4 indexed citations
17.
Shah, Ankit, et al.. (2011). Chronic Urticaria Related to Menses. Journal of Allergy and Clinical Immunology. 127(2). AB102–AB102.
18.
Shah, Ankit, et al.. (2011). Fault Tolerance in Cluster Computing System. 408–412. 2 indexed citations
19.
Ambawade, Dayanand, et al.. (2010). Statistical Tuning of Walfisch-Ikegami Model in Urban and Suburban Environments. vt 29. 538–543. 8 indexed citations
20.
Shah, Ankit, et al.. (2008). Comparative bioactivity studies on two Mimosa species. Boletin Latinoamericano y del Caribe de plantas Medicinales y Aromaticas. 7(1). 38–43. 23 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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