Megha Khosla

64 total papers · 612 total citations
25 papers, 293 citations indexed

About

Megha Khosla is a scholar working on Artificial Intelligence, Molecular Biology and Computer Networks and Communications. According to data from OpenAlex, Megha Khosla has authored 25 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 6 papers in Molecular Biology and 4 papers in Computer Networks and Communications. Recurrent topics in Megha Khosla's work include Advanced Graph Neural Networks (8 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Cancer-related molecular mechanisms research (3 papers). Megha Khosla is often cited by papers focused on Advanced Graph Neural Networks (8 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Cancer-related molecular mechanisms research (3 papers). Megha Khosla collaborates with scholars based in Germany, Netherlands and India. Megha Khosla's co-authors include Avishek Anand, Vinay Setty, Gisa Gerold, Graham Brogden, Κωνσταντίνος Παναγιώτου, T. Mukai, Shinsuke Koyama, Nikolaos Fountoulakis, Tim Byrnes and Koustav Rudra and has published in prestigious journals such as Scientific Reports, BMC Bioinformatics and Cell Reports.

In The Last Decade

Megha Khosla

22 papers receiving 287 citations

Author Peers

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

Author						Papers	Cites
Megha Khosla	187	63	42	27	25	25	293
Antonio Messina	118 0.6×	89 1.4×	88 2.1×	30 1.1×	15 0.6×	28	278
Wei Liu	113 0.6×	45 0.7×	28 0.7×	23 0.9×	15 0.6×	25	325
Bo-Lun Chen	65 0.3×	15 0.2×	70 1.7×	14 0.5×	47 1.9×	35	310
Thomy Phan	64 0.3×	59 0.9×	43 1.0×	22 0.8×	10 0.4×	26	320
Kartik Venkat	124 0.7×	29 0.5×	9 0.2×	65 2.4×	17 0.7×	21	253
Wen-Xiang Chen	96 0.5×	33 0.5×	15 0.4×	13 0.5×	24 1.0×	35	218
Blair D. Sullivan	136 0.7×	42 0.7×	16 0.4×	36 1.3×	31 1.2×	29	278
Koji Nuida	169 0.9×	19 0.3×	38 0.9×	12 0.4×	58 2.3×	43	251
Ying Yin	50 0.3×	128 2.0×	11 0.3×	23 0.9×	8 0.3×	33	348
Xun Jian	183 1.0×	25 0.4×	23 0.5×	60 2.2×	41 1.6×	22	312

Countries citing papers authored by Megha Khosla

Since Specialization

Citations

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

Fields of papers citing papers by Megha Khosla

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Megha Khosla

This figure shows the co-authorship network connecting the top 25 collaborators of Megha Khosla. A scholar is included among the top collaborators of Megha Khosla 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 Megha Khosla. Megha Khosla 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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