Dan Păun

877 citations
14 papers · 477 · 1 hit paper · h-index 6

Impact in

Papers in

Dan Păun

12 papers receiving 439 citations

Dan Păun's Hit Papers

Exploring Opportunities and Challenges of Artificial Intelligence and Machine Learning in Higher Education Institutions 2021 · 265 citations
2650+1+3Years since publication50100150200250

Peers

Dan Păun
Comparison fields: 5 of 76
  • Health Informatics 78
  • Computer Science Applications 145
  • Human-Computer Interaction 38
  • Physical Therapy, Sports Therapy and Rehabilitation 21
  • Information Systems 95
Replace Valentin Kuleto with:
Valentin Kuleto Serbia
Marko Ranković Serbia
Agariadne Dwinggo Samala Indonesia
Ayşe Aslan United Kingdom
M. Elena Rodríguez Spain
Tianchong Wang Hong Kong
Rommel AlAli Saudi Arabia
Sharon Kerr Australia
Agostino Marengo Italy
Anna Bilyatdinova Russia
Dan Păun relative to Valentin Kuleto Serbia Valentin Kuleto's profile →
Citations per field
00.5×3.5×
Valentin Kuleto · 1×
Citations per year

Countries citing papers authored by Dan Păun

Since Specialization
Citations

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

Fields of papers citing papers by Dan Păun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside Dan Păun, 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 Dan Păun Line = papers co-authored together Dan Păun links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1
Exploring Opportunities and Challenges of Artificial Intelligence and Machine Learning in Higher Education Institutions
Hit paper breakdown →
2021265
2 202264
3 202157
4 202145
5 202230
6 20237
7 20243
8 20222
9 20231
10 20221
11 20211
12 20221
13 20220
14 20250

About Dan Păun

Dan Păun is a scholar working on Physical Therapy, Sports Therapy and Rehabilitation, Computer Science Applications, Social Psychology, Management Information Systems and Economics and Econometrics, having authored 14 papers that have together received 477 indexed citations. Recurring topics across this work include Sports and Physical Education Research (3 papers), Online Learning and Analytics (3 papers), Big Data and Business Intelligence (2 papers), Augmented Reality Applications (1 paper), Recreation, Leisure, Wilderness Management (1 paper), Physical Education and Training Studies (1 paper), Educational Games and Gamification (1 paper) and Sustainability in Higher Education (1 paper). The work is most often cited by research in Health Informatics (78 citations), Computer Science Applications (145 citations), Human-Computer Interaction (38 citations), Physical Therapy, Sports Therapy and Rehabilitation (21 citations) and Information Systems (95 citations). Dan Păun has collaborated with scholars based in Romania, Serbia and Portugal. Frequent co-authors include Milena Ilić, Valentin Kuleto, Marko Ranković, Oliva Martins, Larisa Mihoreanu, Rocsana Bucea-Manea-Țoniş and Ioan Turcu. Their work appears in journals such as Sustainability and Education Sciences.

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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