Daniel O’Malley

2.6k citations
106 papers · 1.6k indexed · h-index 24

Daniel O’Malley

100 papers receiving 1.6k citations

Peers

Daniel O’Malley
Comparison fields: 5 of 107
  • Environmental Engineering 476
  • Ocean Engineering 319
  • Computational Mathematics 12
  • Statistics, Probability and Uncertainty 135
  • Statistical and Nonlinear Physics 231
Replace F. R. de Hoog with:
F. R. de Hoog Australia
Massimiliano Ferronato Italy
Jocelyne Erhel France
Xiaodong Luo Norway
Richard E. Ewing United States
Robert Eymard France
Yalchin Efendiev United States
Knut‐Andreas Lie Norway
Matthew W. Farthing United States
Gianmarco Manzini Italy
Daniel O’Malley relative to F. R. de Hoog Australia F. R. de Hoog's profile →
Citations per field
00.5×10×12.8×
F. R. de Hoog · 1×
Citations per year

Countries citing papers authored by Daniel O’Malley

Since Specialization
Citations

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

Fields of papers citing papers by Daniel O’Malley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20241
4 20243
5 20242
6 20243
7 20242
8 20242
9 20232
10 202328
11 202324
12 20236
13 202312
14 202210
15
Physics-Informed Machine Learning for Real-time Reservoir Management.
20203
16
Semi-supervised Machine Learning for Analysis of Hydrogeochemical Data and Models
20171
17
Model Analysis of Complex Systems Behavior using MADS
20162
18 201620
19 2016123
20
A Computationally Efficient Parallel Levenberg-Marquardt Algorithm for Large-Scale Big-Data Inversion
20151

About Daniel O’Malley

Daniel O’Malley is a scholar working on Computational Mathematics, Environmental Engineering, Statistical and Nonlinear Physics, Modeling and Simulation and Ocean Engineering, having authored 106 papers that have together received 1.6k indexed citations. Recurring topics across this work include Groundwater flow and contamination studies (36 papers), Hydraulic Fracturing and Reservoir Analysis (21 papers), Quantum Computing Algorithms and Architecture (15 papers), Reservoir Engineering and Simulation Methods (13 papers), Seismic Imaging and Inversion Techniques (12 papers), Model Reduction and Neural Networks (11 papers), Geophysical and Geoelectrical Methods (8 papers) and Fractional Differential Equations Solutions (8 papers). The work is most often cited by research in Environmental Engineering (476 citations), Ocean Engineering (319 citations), Computational Mathematics (12 citations), Statistics, Probability and Uncertainty (135 citations) and Statistical and Nonlinear Physics (231 citations). Daniel O’Malley has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Velimir V. Vesselinov, Hari Viswanathan, Satish Karra, John H. Cushman, Jeffrey D. Hyman, G. Srinivasan, Boian S. Alexandrov, Esteban Rougier, John Golden and Teeratorn Kadeethum. Their work appears in journals such as Scientific Reports, Water Resources Research, Advances in Water Resources, Computational Materials Science and Journal of Statistical Physics.

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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