Daniel Ullman

32 papers receiving 1.1k citations

Peers

Daniel Ullman
Comparison fields: 5 of 76
  • Social Psychology 598
  • Human-Computer Interaction 131
  • Safety Research 162
  • Clinical Psychology 291
  • Artificial Intelligence 312
Replace Elizabeth S. Kim with:
Elizabeth S. Kim United States
Kensuke Kato Japan
Rebecca Stafford New Zealand
Hadas Erel Israel
Lynne Hall United Kingdom
Rosemarijn Looije Netherlands
Maha Salem United Kingdom
Solace Shen United States
Paul Baxter United Kingdom
Carlos Martinho Portugal
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Citations per field
00.5×2.7×
Elizabeth S. Kim · 1×
Citations per year

Countries citing papers authored by Daniel Ullman

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Ullman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018147
2 2007100
3 201889
4 201876
5 201574
6 200969
7 201861
8 201556
9 201954
10 201140
11 201738
12 201236
13 201734
14 202033
15 201530
16 200828
17 201325
18 201722
19
Smart Human, Smarter Robot: How Cheating Affects Perceptions of Social Agency
201421
20 202120

About Daniel Ullman

Daniel Ullman is a scholar working on Social Psychology, Sociology and Political Science, Cognitive Neuroscience, Safety Research and Clinical Psychology, having authored 32 papers that have together received 1.1k indexed citations. Recurring topics across this work include Social Robot Interaction and HRI (13 papers), Ethics and Social Impacts of AI (7 papers), Human-Automation Interaction and Safety (6 papers), Psychopathy, Forensic Psychiatry, Sexual Offending (6 papers), Criminal Justice and Corrections Analysis (5 papers), Psychology of Moral and Emotional Judgment (4 papers), Face Recognition and Perception (4 papers) and Gaze Tracking and Assistive Technology (3 papers). The work is most often cited by research in Social Psychology (598 citations), Human-Computer Interaction (131 citations), Safety Research (162 citations), Clinical Psychology (291 citations) and Artificial Intelligence (312 citations). Daniel Ullman has collaborated with scholars based in United States and Canada. Frequent co-authors include Bertram F. Malle, Elizabeth Phillips, Mario J. Scalora, Jodi L. Viljoen, Brian Scassellati, Xuan Zhao, Iolanda Leite, Stefanie Tellex, Nicole Salomons and Marissa McCoy. Their work appears in journals such as Sexual Abuse, Cognitive Science, Criminal Justice and Behavior, International Journal of Forensic Mental Health and ACM Transactions on Interactive Intelligent Systems.

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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