Disha Makhija

16 total papers · 469 total citations
2 papers, 245 citations indexed

About

Disha Makhija is a scholar working on Artificial Intelligence, Sociology and Political Science and Information Systems. According to data from OpenAlex, Disha Makhija has authored 2 papers receiving a total of 245 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Sociology and Political Science and 1 paper in Information Systems. Recurrent topics in Disha Makhija's work include Machine Learning and Algorithms (1 paper), Advanced Graph Neural Networks (1 paper) and Adversarial Robustness in Machine Learning (1 paper). Disha Makhija is often cited by papers focused on Machine Learning and Algorithms (1 paper), Advanced Graph Neural Networks (1 paper) and Adversarial Robustness in Machine Learning (1 paper). Disha Makhija collaborates with scholars based in United States and Germany. Disha Makhija's co-authors include Christos Faloutsos, Bryan Hooi, Srijan Kumar, Mohit Kumar, V. S. Subrahmanian and Stephan Günnemann and has published in prestigious journals such as Proceedings of the VLDB Endowment.

In The Last Decade

Disha Makhija

2 papers receiving 242 citations

Hit Papers

REV2 2018 2026 2020 2023 2018 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation benchmark for papers published in the same subfield and year, or reaches the top citation threshold in at least one of its specific research topics.

  1. REV2
    2018 210 citations Srijan Kumar, Bryan Hooi et al. profile →

Author Peers

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

Author Last Decade Papers Cites
Disha Makhija 159 124 88 42 38 2 245
Mohit Kumar 136 0.9× 111 0.9× 78 0.9× 36 0.9× 38 1.0× 5 223
Timothy La Fond 123 0.8× 160 1.3× 55 0.6× 38 0.9× 27 0.7× 7 243
Hwanjo Yu 173 1.1× 90 0.7× 102 1.2× 69 1.6× 11 0.3× 5 265
Yiye Ruan 109 0.7× 129 1.0× 57 0.6× 44 1.0× 23 0.6× 9 218
Matjaž Zaveršnik 98 0.6× 165 1.3× 67 0.8× 76 1.8× 18 0.5× 4 288
Ravi Kumar 124 0.8× 79 0.6× 35 0.4× 45 1.1× 30 0.8× 8 249
Hsinchun Chen 141 0.9× 42 0.3× 104 1.2× 16 0.4× 50 1.3× 7 273
Ofrit Lesser 112 0.7× 145 1.2× 49 0.6× 46 1.1× 33 0.9× 8 239
Eldar Sadikov 106 0.7× 77 0.6× 122 1.4× 30 0.7× 41 1.1× 6 275
Wei Xie 153 1.0× 164 1.3× 79 0.9× 32 0.8× 28 0.7× 8 250

Countries citing papers authored by Disha Makhija

Since Specialization
Citations

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

Fields of papers citing papers by Disha Makhija

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Disha Makhija

This figure shows the co-authorship network connecting the top 25 collaborators of Disha Makhija. A scholar is included among the top collaborators of Disha Makhija 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 Disha Makhija. Disha Makhija 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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2026