Udayan Khurana

42 total papers · 1.0k total citations
27 papers, 595 citations indexed

About

Udayan Khurana is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Networks and Communications. According to data from OpenAlex, Udayan Khurana has authored 27 papers receiving a total of 595 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 9 papers in Management Science and Operations Research and 8 papers in Computer Networks and Communications. Recurrent topics in Udayan Khurana's work include Data Quality and Management (9 papers), Advanced Database Systems and Queries (8 papers) and Machine Learning and Data Classification (8 papers). Udayan Khurana is often cited by papers focused on Data Quality and Management (9 papers), Advanced Database Systems and Queries (8 papers) and Machine Learning and Data Classification (8 papers). Udayan Khurana collaborates with scholars based in United States, Canada and Ireland. Udayan Khurana's co-authors include Horst Samulowitz, Deepak S. Turaga, Amol Deshpande, Elias B. Khalil, Fatemeh Nargesian, Sainyam Galhotra, Kavitha Srinivas, Srinivasan Parthasarathy, Miao Qi and B. Shneiderman and has published in prestigious journals such as Proceedings of the VLDB Endowment, ACM Transactions on Software Engineering and Methodology and arXiv (Cornell University).

In The Last Decade

Udayan Khurana

25 papers receiving 559 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Udayan Khurana	313	173	147	104	102	27	595
Parikshit Ram	312 1.0×	227 1.3×	72 0.5×	104 1.0×	123 1.2×	35	655
Štefan Dlugolinský	244 0.8×	73 0.4×	127 0.9×	62 0.6×	110 1.1×	25	646
Wubai Zhou	341 1.1×	94 0.5×	157 1.1×	49 0.5×	226 2.2×	24	665
Alessandra Mileo	276 0.9×	162 0.9×	223 1.5×	56 0.5×	135 1.3×	49	656
Jai E. Jung	167 0.5×	127 0.7×	125 0.9×	60 0.6×	142 1.4×	23	561
Nitin Gupta	217 0.7×	122 0.7×	169 1.1×	70 0.7×	164 1.6×	45	618
Ramzan Talib	282 0.9×	115 0.7×	74 0.5×	44 0.4×	137 1.3×	26	653
Yan Liu	242 0.8×	94 0.5×	153 1.0×	104 1.0×	141 1.4×	63	591
Leslie F. Sikos	294 0.9×	112 0.6×	243 1.7×	177 1.7×	207 2.0×	38	583
Amélie Gyrard	265 0.8×	101 0.6×	204 1.4×	27 0.3×	160 1.6×	32	577

Countries citing papers authored by Udayan Khurana

Since Specialization

Citations

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

Fields of papers citing papers by Udayan Khurana

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Udayan Khurana

This figure shows the co-authorship network connecting the top 25 collaborators of Udayan Khurana. A scholar is included among the top collaborators of Udayan Khurana 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 Udayan Khurana. Udayan Khurana is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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