E.M. Oblow

1.1k citations
51 papers · 538 · h-index 14

Impact in

Papers in

E.M. Oblow

43 papers receiving 471 citations

Peers

E.M. Oblow
Comparison fields: 5 of 73
  • Statistics, Probability and Uncertainty 99
  • Aerospace Engineering 211
  • Radiation 67
  • Statistical and Nonlinear Physics 51
  • Metals and Alloys 9
Replace Jeffery Lewins with:
Jeffery Lewins United Kingdom
John E. Bussoletti United States
T.H.J.J. van der Hagen Netherlands
D. Ginestar Spain
Todd S. Palmer United States
A. Dubi Israel
Aashwin Mishra United States
Maria Rightley United States
Kenneth D. Jarman United States
A. Premoli Italy
E.M. Oblow relative to Jeffery Lewins United Kingdom Jeffery Lewins's profile →
Citations per field
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Jeffery Lewins · 1×
Citations per year

Countries citing papers authored by E.M. Oblow

Since Specialization
Citations

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

Fields of papers citing papers by E.M. Oblow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside E.M. Oblow, 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 E.M. Oblow Line = papers co-authored together E.M. Oblow 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 1980100
2 199053
3 197840
4 197834
5 197827
6 197626
7
Improved Ferrite Number prediction in stainless steel arc welds using artificial neural networks - Part 2 : Neural network results
200022
8 198822
9 198621
10 198716
11 197515
12 197415
13 199613
14 197813
15
Machine intelligence for robotics applications
19859
16 19769
17 19749
18 19949
19 19949
20 19748

About E.M. Oblow

E.M. Oblow is a scholar working on Artificial Intelligence, Aerospace Engineering, Materials Chemistry, Control and Systems Engineering and Radiation, having authored 51 papers that have together received 538 indexed citations. Recurring topics across this work include Nuclear reactor physics and engineering (13 papers), Machine Learning and Algorithms (11 papers), Machine Learning and Data Classification (7 papers), Fusion materials and technologies (7 papers), Nuclear Materials and Properties (6 papers), Nuclear Physics and Applications (5 papers), Imbalanced Data Classification Techniques (5 papers) and Multi-Criteria Decision Making (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (99 citations), Aerospace Engineering (211 citations), Radiation (67 citations), Statistical and Nonlinear Physics (51 citations) and Metals and Alloys (9 citations). E.M. Oblow has collaborated with scholars based in United States and Israel. Frequent co-authors include J.H. Marable, M. Beckerman, Dan Gabriel Cacuci, C.F. Weber, Nageswara S. V. Rao, E. Greenspan, F.G. Pin, R.Q. Wright, J.M. Vitek and C.R. Weisbin. Their work appears in journals such as Nuclear Science and Engineering, International Journal of General Systems, Machine Learning, Nuclear Fusion and IEEE Transactions on Robotics and Automation.

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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