E.M. Oblow

1.1k citations
57 papers · 612 · h-index 14

Impact in

Papers in

E.M. Oblow

47 papers receiving 521 citations

Peers

E.M. Oblow
Comparison fields: 5 of 78
  • Statistics, Probability and Uncertainty 107
  • Aerospace Engineering 234
  • Radiation 75
  • Statistical and Nonlinear Physics 55
  • Metals and Alloys 9
Replace John E. Bussoletti with:
John E. Bussoletti United States
Jeffery Lewins United Kingdom
D. Ginestar Spain
A. Premoli Italy
T.H.J.J. van der Hagen Netherlands
A. Dubi Israel
Maria Rightley United States
Wolfgang Wöger Germany
Kostadin Ivanov United States
Kenneth D. Jarman United States
E.M. Oblow relative to John E. Bussoletti United States John E. Bussoletti's profile →
Citations per field
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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 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1980109
2 199057
3 197842
4 197838
5 197630
6 197829
7 198825
8
Improved Ferrite Number prediction in stainless steel arc welds using artificial neural networks - Part 2 : Neural network results
200023
9 198623
10 198720
11 197418
12 197517
13 199616
14 197815
15 197412
16 199411
17 199411
18 197610
19 199210
20
Machine intelligence for robotics applications
198510

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 57 papers that have together received 612 indexed citations. Recurring topics across this work include Nuclear reactor physics and engineering (16 papers), Machine Learning and Algorithms (11 papers), Nuclear Materials and Properties (7 papers), Fusion materials and technologies (7 papers), Machine Learning and Data Classification (7 papers), Nuclear Physics and Applications (6 papers), Multi-Criteria Decision Making (5 papers) and Imbalanced Data Classification Techniques (5 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (107 citations), Aerospace Engineering (234 citations), Radiation (75 citations), Statistical and Nonlinear Physics (55 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, C.R. Weisbin and F.R. Mynatt. Their work appears in journals such as Nuclear Science and Engineering, International Journal of General Systems, Nuclear Fusion, Machine Learning 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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