David E. Hubbard

36 papers receiving 438 citations

Peers

David E. Hubbard
Comparison fields: 5 of 103
  • Bioengineering 118
  • Electrochemistry 75
  • Neurology 167
  • Library and Information Sciences 14
  • Internal Medicine 26
Replace Philip Robinson with:
Philip Robinson France
Delia Waldenmaier Germany
Wei Jiao China
Mohamed Mostafa Kotb Egypt
Jonathan D. Ravid United States
Amita Garg India
Ziwei Nie China
Fengzhen Li China
Tzu‐Yen Huang Taiwan
Hirohisa Abe Japan
David E. Hubbard relative to Philip Robinson France Philip Robinson's profile →
Citations per field
00.5×5×10×15×20×25×
Philip Robinson · 1×
Citations per year

Countries citing papers authored by David E. Hubbard

Since Specialization
Citations

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

Fields of papers citing papers by David E. Hubbard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David E. Hubbard. 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 David E. Hubbard. The network helps show where David E. Hubbard may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994134
2 201251
3 201447
4 201231
5 201226
6 201224
7 201316
8 195816
9 201315
10 201113
11 201312
12 201912
13 20148
14 20196
15 20175
16
Collaborative Data Literacy Education for Research Labs: A Case Study at a Large Research University
20214
17 20184
18 20183
19 20123
20
Forecasting Process at Apple Computer
19923

About David E. Hubbard

David E. Hubbard is a scholar working on Statistics, Probability and Uncertainty, Computer Science Applications, Information Systems, Neurology and Library and Information Sciences, having authored 37 papers that have together received 458 indexed citations. Recurring topics across this work include Cerebral Venous Sinus Thrombosis (8 papers), scientometrics and bibliometrics research (8 papers), Open Education and E-Learning (5 papers), Algebraic Geometry and Number Theory (4 papers), Library Science and Information Literacy (4 papers), Library Collection Development and Digital Resources (4 papers), Web visibility and informetrics (3 papers) and Vascular Malformations Diagnosis and Treatment (3 papers). The work is most often cited by research in Bioengineering (118 citations), Electrochemistry (75 citations), Neurology (167 citations), Library and Information Sciences (14 citations) and Internal Medicine (26 citations). David E. Hubbard has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include Patrick J. Kinlen, Ewart Mark Haacke, Wei Feng, David T. Utriainen, Zahid Latif, Gabriela Trifan, Jane Stephens, Yashwanth Katkuri, Ziv J. Haskal and Michael D. Dake. Their work appears in journals such as Journal of Vascular and Interventional Radiology, The Journal of Academic Librarianship, Journal of Number Theory, Science & Technology Libraries and Proceedings of the American Society for Information Science and Technology.

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.

Explore authors with similar magnitude of impact