Omer San

5.3k total citations · 1 hit paper
125 papers, 3.4k citations indexed

About

Omer San is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Atmospheric Science. According to data from OpenAlex, Omer San has authored 125 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Computational Mechanics, 52 papers in Statistical and Nonlinear Physics and 30 papers in Atmospheric Science. Recurrent topics in Omer San's work include Model Reduction and Neural Networks (50 papers), Fluid Dynamics and Turbulent Flows (49 papers) and Meteorological Phenomena and Simulations (29 papers). Omer San is often cited by papers focused on Model Reduction and Neural Networks (50 papers), Fluid Dynamics and Turbulent Flows (49 papers) and Meteorological Phenomena and Simulations (29 papers). Omer San collaborates with scholars based in United States, Norway and Romania. Omer San's co-authors include Adil Rasheed, Trond Kvamsdal, Romit Maulik, Suraj Pawar, Traian Iliescu, Anne Staples, Sk. Mashfiqur Rahman, Kursat Kara, Shady E. Ahmed and Prakash Vedula and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Fluid Mechanics.

In The Last Decade

Omer San

120 papers receiving 3.3k citations

Hit Papers

Digital Twin: Values, Challenges and Enablers From a Mode... 2020 2026 2022 2024 2020 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
    2020 1.0k citations Adil Rasheed, Omer San et al. IEEE Access profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Omer San United States 30 1.2k 1.1k 650 344 333 125 3.4k
Adil Rasheed Norway 24 660 0.5× 550 0.5× 657 1.0× 473 1.4× 125 0.4× 144 3.0k
Trond Kvamsdal Norway 24 1.3k 1.1× 237 0.2× 613 0.9× 386 1.1× 100 0.3× 85 3.1k
András Sóbester United Kingdom 17 586 0.5× 355 0.3× 242 0.4× 814 2.4× 59 0.2× 75 4.3k
Alexander I. J. Forrester United Kingdom 21 733 0.6× 602 0.5× 298 0.5× 1.0k 3.0× 49 0.1× 51 6.3k
Shigeru Obayashi Japan 37 3.0k 2.4× 279 0.2× 130 0.2× 2.5k 7.4× 185 0.6× 366 5.3k
Jacques Périaux France 33 3.2k 2.7× 210 0.2× 99 0.2× 542 1.6× 48 0.1× 169 5.0k
Christopher J. Roy United States 27 2.8k 2.3× 375 0.3× 48 0.1× 1.5k 4.2× 163 0.5× 183 4.6k
Patrick Koch United States 19 184 0.2× 114 0.1× 369 0.6× 324 0.9× 168 0.5× 72 3.2k
Anima Anandkumar United States 28 322 0.3× 365 0.3× 62 0.1× 235 0.7× 95 0.3× 118 2.9k
Eleni Chatzi Switzerland 44 464 0.4× 362 0.3× 93 0.1× 301 0.9× 41 0.1× 333 6.6k

Countries citing papers authored by Omer San

Since Specialization
Citations

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

Fields of papers citing papers by Omer San

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Omer San

This figure shows the co-authorship network connecting the top 25 collaborators of Omer San. A scholar is included among the top collaborators of Omer San based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Omer San. Omer San is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bradshaw, Craig R., et al.. (2024). A gray-box model for unitary air conditioners developed with symbolic regression. International Journal of Refrigeration. 168. 696–707. 11 indexed citations
2.
Rasheed, Adil, Mandar Tabib, Kjetil Johannessen, et al.. (2024). Digital Twin for Wind Energy: Latest Updates From the NorthWind Project. 1 indexed citations
3.
Rasheed, Adil, et al.. (2024). Enhancing elasticity models with deep learning: A novel corrective source term approach for accurate predictions. Applied Soft Computing. 153. 111312–111312. 2 indexed citations
4.
Rasheed, Adil, et al.. (2024). Enhancing wind field resolution in complex terrain through a knowledge-driven machine learning approach. Engineering Applications of Artificial Intelligence. 137. 109167–109167. 2 indexed citations
5.
San, Omer, et al.. (2023). Blending machine learning and sequential data assimilation over latent spaces for surrogate modeling of Boussinesq systems. Physica D Nonlinear Phenomena. 448. 133711–133711. 3 indexed citations
6.
Rasheed, Adil, et al.. (2023). Artificial Intelligence-Driven Digital Twin of a Modern House Demonstrated in Virtual Reality. IEEE Access. 11. 35035–35058. 17 indexed citations
7.
Pawar, Suraj, et al.. (2022). Physics guided neural networks for modelling of non-linear dynamics. Neural Networks. 154. 333–345. 46 indexed citations
8.
Pawar, Suraj & Omer San. (2022). Equation‐Free Surrogate Modeling of Geophysical Flows at the Intersection of Machine Learning and Data Assimilation. Journal of Advances in Modeling Earth Systems. 14(11). 14 indexed citations
9.
Rasheed, Adil, et al.. (2022). Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach. Applied Soft Computing. 128. 109533–109533. 32 indexed citations
10.
San, Omer, Suraj Pawar, & Adil Rasheed. (2022). Prospects of federated machine learning in fluid dynamics. AIP Advances. 12(9). 5 indexed citations
11.
Pawar, Suraj & Omer San. (2021). Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows. Physical Review Fluids. 6(5). 24 indexed citations
12.
San, Omer, Adil Rasheed, & Trond Kvamsdal. (2021). Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution. GAMM-Mitteilungen. 44(2). 43 indexed citations
13.
Rasheed, Adil, et al.. (2020). Feature engineering and symbolic regression methods for detecting hidden physics from sparse sensor observation data. Duo Research Archive (University of Oslo). 54 indexed citations
14.
Rasheed, Adil, et al.. (2020). Taming an Autonomous Surface Vehicle for Path Following and Collision Avoidance Using Deep Reinforcement Learning. IEEE Access. 8. 41466–41481. 57 indexed citations
15.
Rasheed, Adil, Omer San, & Trond Kvamsdal. (2020). Digital Twin: Values, Challenges and Enablers From a Modeling Perspective. IEEE Access. 8. 21980–22012. 1025 indexed citations breakdown →
16.
Rasheed, Adil, et al.. (2020). COLREG-Compliant Collision Avoidance for Unmanned Surface Vehicle Using Deep Reinforcement Learning. IEEE Access. 8. 165344–165364. 64 indexed citations
17.
Pawar, Suraj, Shady E. Ahmed, Omer San, Adil Rasheed, & I. M. Navon. (2020). Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows. Physics of Fluids. 32(7). 38 indexed citations
18.
Ahmed, Shady E., et al.. (2020). Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction. Physical review. E. 102(4). 43302–43302. 2 indexed citations
19.
Ahmed, Shady E., Sk. Mashfiqur Rahman, Omer San, Adil Rasheed, & I. M. Navon. (2019). Memory embedded non-intrusive reduced order modeling of non-ergodic flows. Physics of Fluids. 31(12). 37 indexed citations
20.
Pawar, Suraj, Omer San, & Adil Rasheed. (2019). Deep learning based sub-grid scale closure for LES of Kraichnan turbulence. Bulletin of the American Physical Society. 1 indexed citations

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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