Huma Shah

43 papers receiving 478 citations

Peers

Huma Shah
Comparison fields: 5 of 84
  • Safety Research 131
  • Health Informatics 17
  • Social Psychology 150
  • Artificial Intelligence 208
  • Computational Theory and Mathematics 92
Replace Suzanne Tolmeijer with:
Suzanne Tolmeijer Switzerland
Thomas M. Arnold United States
Bruce M. McLaren Germany
Emiliano Lorini France
Nancy Fulda United States
Sara Moussawi United States
Ruotong Wang United States
Joo-Wha Hong United States
Hope Schroeder United States
Gert‐Jan C. Lokhorst Netherlands
Huma Shah relative to Suzanne Tolmeijer Switzerland Suzanne Tolmeijer's profile →
Citations per field
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Suzanne Tolmeijer · 1×
Citations per year

Countries citing papers authored by Huma Shah

Since Specialization
Citations

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

Fields of papers citing papers by Huma Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Huma Shah, 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 Huma Shah Line = papers co-authored together Huma Shah links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016100
2 201561
3 201428
4 201027
5
Exploring the Impediments of Successful ERP Implementation: A Case Study in a Public Organization
201124
6 201322
7 201321
8 201021
9 201520
10 201417
11 201617
12 201515
13
Guidelines on Regulating Robotics
201413
14 199911
15
From the Buzzing in Turing’s Head to Machine Intelligence Contests
20109
16 20179
17 20108
18
The impact of culture in enterprise resource planning system implementation
20138
19
Tracker: a framework to support reducing rework through decision management
20037
20 20147

About Huma Shah

Huma Shah is a scholar working on Computational Theory and Mathematics, Safety Research, Social Psychology, Artificial Intelligence and Information Systems, having authored 51 papers that have together received 524 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (17 papers), Computability, Logic, AI Algorithms (17 papers), Social Robot Interaction and HRI (9 papers), AI in Service Interactions (7 papers), Deception detection and forensic psychology (4 papers), Neuroethics, Human Enhancement, Biomedical Innovations (4 papers), User Authentication and Security Systems (3 papers) and Business Process Modeling and Analysis (2 papers). The work is most often cited by research in Safety Research (131 citations), Health Informatics (17 citations), Social Psychology (150 citations), Artificial Intelligence (208 citations) and Computational Theory and Mathematics (92 citations). Huma Shah has collaborated with scholars based in United Kingdom, Spain and Finland. Frequent co-authors include Kevin Warwick, Jordi Vallverdú, Defeng Wu, James H. Moor, Abdul Zahid Khan, Bernadette Sharp, Alan Dix, Stephen R. Gulliver, Christopher S. Chapman and Pericle Salvini. Their work appears in journals such as AI & Society, Kybernetes, Minds and Machines, International Orthopaedics and IEEE Transactions on Computational Intelligence and AI in Games.

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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