Vidushi Marda

406 citations
11 papers · 193 · h-index 7

Impact in

Papers in

    • Ethics and Social Impacts of AI 8
    • Law, AI, and Intellectual Property 2
    • Explainable Artificial Intelligence (XAI) 2
    • Privacy-Preserving Technologies in Data 1

Vidushi Marda

10 papers receiving 170 citations

Peers

Vidushi Marda
Comparison fields: 5 of 52
  • Health Informatics 22
  • Safety Research 81
  • Communication 14
  • Computer Science Applications 9
  • Management Information Systems 14
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Elettra Bietti United States
Kevin Bauer Germany
Nicola Lucchi Spain
Xavier Ferrer United Kingdom
Konrad Sowa Poland
Daan Kolkman Netherlands
Jascha Bareis Germany
Federico Casolari Italy
William Welser
Valdemar Pinho Neto Brazil
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Citations per year

Countries citing papers authored by Vidushi Marda

Since Specialization
Citations

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

Fields of papers citing papers by Vidushi Marda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Vidushi Marda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Vidushi Marda Line = papers co-authored together Vidushi Marda links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 201864
2
Artificial Intelligence Governance and Ethics : Global Perspectives
201926
3 202026
4 202121
5 201819
6 202014
7
Wisdom of the Crowd: Multistakeholder Perspectives on the Fake News Debate
201813
8 20224
9 20203
10 20172
11 20141

About Vidushi Marda

Vidushi Marda is a scholar working on Safety Research, Artificial Intelligence, Information Systems, Sociology and Political Science and Communication, having authored 11 papers that have together received 193 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (8 papers), Blockchain Technology Applications and Security (2 papers), Law, AI, and Intellectual Property (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Neuroethics, Human Enhancement, Biomedical Innovations (1 paper), Privacy-Preserving Technologies in Data (1 paper), Artificial Intelligence in Healthcare and Education (1 paper) and Social Media and Politics (1 paper). The work is most often cited by research in Health Informatics (22 citations), Safety Research (81 citations), Communication (14 citations), Computer Science Applications (9 citations) and Management Information Systems (14 citations). Vidushi Marda has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Stefanía Milan, Thilo Hagendorff, Monique Mann, Angela Daly, Ben Wagner, Saskia Witteborn, Hui Li, Corinne Cath, Mark Latonero and Risto Miikkulainen. Their work appears in journals such as Nature Machine Intelligence, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Jurisprudencija, SSRN Electronic Journal and Strathprints: The University of Strathclyde institutional repository (University of Strathclyde).

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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