Mahima Pushkarna

24 total papers · 1.2k total citations
11 papers, 533 citations indexed

About

Mahima Pushkarna is a scholar working on Artificial Intelligence, Safety Research and Information Systems. According to data from OpenAlex, Mahima Pushkarna has authored 11 papers receiving a total of 533 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 3 papers in Safety Research and 2 papers in Information Systems. Recurrent topics in Mahima Pushkarna's work include Topic Modeling (5 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Natural Language Processing Techniques (3 papers). Mahima Pushkarna is often cited by papers focused on Topic Modeling (5 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Natural Language Processing Techniques (3 papers). Mahima Pushkarna collaborates with scholars based in United States, United Kingdom and Canada. Mahima Pushkarna's co-authors include James Wexler, Tolga Bolukbasi, Martin Wattenberg, Fernanda Viégas, Andrew Zaldivar, Oddur Kjartansson, Ian Tenney, Emily Reif, Ann Yuan and Sebastian Gehrmann and has published in prestigious journals such as Communications of the ACM and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

Mahima Pushkarna

10 papers receiving 516 citations

Hit Papers

The What-If Tool: Interac... 2019 2026 2021 2023 2019 50 100 150 200 250

Author Peers

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

Author Last Decade Papers Cites
Mahima Pushkarna 365 148 104 88 47 11 533
Upol Ehsan 299 0.8× 149 1.0× 45 0.4× 96 1.1× 37 0.8× 20 469
Daniel Smilkov 252 0.7× 51 0.3× 143 1.4× 67 0.8× 42 0.9× 10 526
Shivani Kapania 230 0.6× 168 1.1× 93 0.9× 59 0.7× 76 1.6× 14 593
Daniel Oster 269 0.7× 128 0.9× 27 0.3× 81 0.9× 47 1.0× 18 525
Alon Jacovi 348 1.0× 142 1.0× 28 0.3× 73 0.8× 66 1.4× 11 495
Ruotong Wang 224 0.6× 193 1.3× 38 0.4× 56 0.6× 71 1.5× 17 480
J.D. Zamfirescu-Pereira 255 0.7× 46 0.3× 55 0.5× 51 0.6× 88 1.9× 21 526
Richard Tomsett 262 0.7× 73 0.5× 36 0.3× 49 0.6× 29 0.6× 17 608
Jacquelyn Martino 228 0.6× 231 1.6× 104 1.0× 75 0.9× 161 3.4× 13 588
Shayak Sen 406 1.1× 98 0.7× 35 0.3× 35 0.4× 78 1.7× 9 575

Countries citing papers authored by Mahima Pushkarna

Since Specialization
Citations

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

Fields of papers citing papers by Mahima Pushkarna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mahima Pushkarna

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