Ramesh Balakrishnan

764 total citations
34 papers, 519 citations indexed

About

Ramesh Balakrishnan is a scholar working on Computational Mechanics, Applied Mathematics and Electrical and Electronic Engineering. According to data from OpenAlex, Ramesh Balakrishnan has authored 34 papers receiving a total of 519 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computational Mechanics, 9 papers in Applied Mathematics and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Ramesh Balakrishnan's work include Fluid Dynamics and Turbulent Flows (10 papers), Computational Fluid Dynamics and Aerodynamics (10 papers) and Gas Dynamics and Kinetic Theory (9 papers). Ramesh Balakrishnan is often cited by papers focused on Fluid Dynamics and Turbulent Flows (10 papers), Computational Fluid Dynamics and Aerodynamics (10 papers) and Gas Dynamics and Kinetic Theory (9 papers). Ramesh Balakrishnan collaborates with scholars based in United States, South Korea and Spain. Ramesh Balakrishnan's co-authors include Ramesh K. Agarwal, Thierry Poinsot, Gabriel Staffelbach, Laurent Gicquel, Pierre Wolf, Anil Pahwa, Hyuck M. Kwon, Romit Maulik, Venkatasubramanian Viswanathan and Kenneth E. Jansen and has published in prestigious journals such as Journal of Fluid Mechanics, Computer Methods in Applied Mechanics and Engineering and Industrial & Engineering Chemistry Research.

In The Last Decade

Ramesh Balakrishnan

30 papers receiving 474 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ramesh Balakrishnan United States 12 358 254 111 60 56 34 519
Qingdong Cai China 15 637 1.8× 311 1.2× 136 1.2× 121 2.0× 15 0.3× 36 737
William B. Bush United States 16 677 1.9× 254 1.0× 329 3.0× 48 0.8× 162 2.9× 55 932
Quang Huy Tran France 12 324 0.9× 138 0.5× 32 0.3× 48 0.8× 18 0.3× 43 530
Aldo Bonfiglioli Italy 14 466 1.3× 245 1.0× 279 2.5× 58 1.0× 19 0.3× 60 668
Renée Gatignol France 10 430 1.2× 270 1.1× 69 0.6× 54 0.9× 8 0.1× 49 621
D. H. Rudy United States 8 494 1.4× 105 0.4× 199 1.8× 56 0.9× 33 0.6× 19 542
Richard B. Pember United States 12 658 1.8× 206 0.8× 105 0.9× 30 0.5× 33 0.6× 20 733
Juan-Chen Huang Taiwan 13 958 2.7× 920 3.6× 287 2.6× 84 1.4× 45 0.8× 37 1.3k
Sabine Roller Germany 12 440 1.2× 119 0.5× 99 0.9× 124 2.1× 7 0.1× 35 589
Guido Lodato France 14 620 1.7× 67 0.3× 228 2.1× 17 0.3× 111 2.0× 34 689

Countries citing papers authored by Ramesh Balakrishnan

Since Specialization
Citations

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

Fields of papers citing papers by Ramesh Balakrishnan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ramesh Balakrishnan

This figure shows the co-authorship network connecting the top 25 collaborators of Ramesh Balakrishnan. A scholar is included among the top collaborators of Ramesh Balakrishnan 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 Ramesh Balakrishnan. Ramesh Balakrishnan 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.
Pal, Pinaki, et al.. (2025). Mesh-based super-resolution of fluid flows with multiscale graph neural networks. Computer Methods in Applied Mechanics and Engineering. 443. 118072–118072. 1 indexed citations
2.
Balakrishnan, Ramesh, et al.. (2023). Differentiable physics-enabled closure modeling for Burgers’ turbulence. Machine Learning Science and Technology. 4(1). 15017–15017. 13 indexed citations
3.
Fang, Jun, et al.. (2020). Annular Flow Simulation Supported by Iterative In-Memory Mesh Adaptation. Nuclear Science and Engineering. 194(8-9). 676–689. 3 indexed citations
4.
Fang, Jun, et al.. (2018). Interface Tracking Investigation of Geometric Effects on the Bubbly Flow in PWR Subchannels. Nuclear Science and Engineering. 193(1-2). 46–62. 13 indexed citations
5.
Mirocha, Jeffrey D., Matthew Churchfield, Domingo Muñoz‐Esparza, et al.. (2018). Large-eddy simulation sensitivities to variations of configuration and forcing parameters in canonical boundary-layer flows for wind energy applications. Wind energy science. 3(2). 589–613. 26 indexed citations
6.
Mirocha, Jeffrey D., Matthew Churchfield, Domingo Muñoz‐Esparza, et al.. (2017). Large-Eddy Simulation Sensitivities to Variations of Configuration and Forcing Parameters in Canonical Boundary-Layer Flows for Wind Energy Applications. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2 indexed citations
7.
Gupta, Himanshu, et al.. (2014). Formulating, implementing and evaluating ERP in small and medium scale industries. ResearchOnline at James Cook University (James Cook University). 5 indexed citations
8.
Wolf, Pierre, Ramesh Balakrishnan, Gabriel Staffelbach, Laurent Gicquel, & Thierry Poinsot. (2011). Using LES to Study Reacting Flows and Instabilities in Annular Combustion Chambers. Flow Turbulence and Combustion. 88(1-2). 191–206. 89 indexed citations
9.
Balakrishnan, Ramesh, E. D’Azevedo, Bronson Messer, et al.. (2006). On the performance of SPAI and ADI-like preconditioners for core collapse supernova simulations in one spatial dimension. Computer Physics Communications. 175(5). 330–338.
10.
Balakrishnan, Ramesh, et al.. (2005). An inverse problem based approach for channel parameters estimation in UWB systems. 2. 1073–1077. 3 indexed citations
11.
Balakrishnan, Ramesh & Hyuck M. Kwon. (2004). Estimation of channel parameters using iterative least squares approach for W-CDMA and UWB systems. 8. 1254–1258. 1 indexed citations
12.
Balakrishnan, Ramesh & Hyuck M. Kwon. (2004). A new inverse problem based approach for azimuthal DOA estimation. 2187–2191. 3 indexed citations
13.
Balakrishnan, Ramesh, et al.. (2003). Knowledge based expert system for forging die design. 6. 498–504.
14.
Balakrishnan, Ramesh, et al.. (2003). Modified maximin algorithm for FH system under fading environments. 32. 652–657. 1 indexed citations
15.
Garcia‐Luna‐Aceves, J.J., et al.. (2002). A Scalable and Fault-Tolerant Architecture for Internet Multicasting Using Meshes. Defense Technical Information Center (DTIC). 87–94. 1 indexed citations
16.
Agarwal, Ramesh K., et al.. (2001). Beyond Navier–Stokes: Burnett equations for flows in the continuum–transition regime. Physics of Fluids. 13(10). 3061–3085. 190 indexed citations
17.
Balakrishnan, Ramesh. (1999). Entropy consistent formulation and numerical simulation of the BGK-Burnett equations for hypersonic flows in the continuum-transition regime. PhDT. 6214. 15 indexed citations
18.
Balakrishnan, Ramesh & Ramesh K. Agarwal. (1999). A comparative study of several higher-order kinetic formulations beyond Navier-Stokes for computing the shock structure. 37th Aerospace Sciences Meeting and Exhibit. 6 indexed citations
19.
Balakrishnan, Ramesh, et al.. (1999). BGK-Burnett Equations for Flows in the Continuum-Transition Regime. Journal of Thermophysics and Heat Transfer. 13(4). 397–410. 21 indexed citations
20.
Balakrishnan, Ramesh & Ramesh K. Agarwal. (1998). Numerical simulation of the BGK-Burnett equations for hypersonic blunt body flows using the kinetic wave-particle flux splitting algorithm. 36th AIAA Aerospace Sciences Meeting and Exhibit. 3 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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