Ádám Rák

1.8k total citations
15 papers, 355 citations indexed

About

Ádám Rák is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Ádám Rák has authored 15 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Electrical and Electronic Engineering, 5 papers in Computer Networks and Communications and 4 papers in Artificial Intelligence. Recurrent topics in Ádám Rák's work include Advanced Memory and Neural Computing (7 papers), Neural Networks Stability and Synchronization (4 papers) and Neural Networks and Applications (3 papers). Ádám Rák is often cited by papers focused on Advanced Memory and Neural Computing (7 papers), Neural Networks Stability and Synchronization (4 papers) and Neural Networks and Applications (3 papers). Ádám Rák collaborates with scholars based in Hungary and United Kingdom. Ádám Rák's co-authors include György Cserey, Gábor János Tornai and Themis Prodromakis and has published in prestigious journals such as Chemical Physics Letters, Journal of Chemical Theory and Computation and Materials.

In The Last Decade

Ádám Rák

14 papers receiving 336 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ádám Rák Hungary 8 228 133 64 50 38 15 355
Christophe Piveteau Switzerland 10 476 2.1× 77 0.6× 40 0.6× 75 1.5× 30 0.8× 20 633
Akiko Ohata Japan 15 626 2.7× 60 0.5× 20 0.3× 69 1.4× 13 0.3× 46 709
Irina Kataeva Japan 13 645 2.8× 238 1.8× 95 1.5× 132 2.6× 33 0.9× 25 740
Qi Qin China 11 754 3.3× 225 1.7× 63 1.0× 39 0.8× 7 0.2× 39 826
Advait Madhavan United States 12 383 1.7× 73 0.5× 37 0.6× 85 1.7× 50 1.3× 37 483
Miguel Ángel Lastras-Montaño United States 10 349 1.5× 138 1.0× 21 0.3× 14 0.3× 16 0.4× 24 363
Zhan Liu United States 6 309 1.4× 48 0.4× 53 0.8× 16 0.3× 36 0.9× 6 391
Д. С. Королев Russia 18 744 3.3× 364 2.7× 210 3.3× 58 1.2× 46 1.2× 84 1.1k
John Suehle United States 2 246 1.1× 90 0.7× 26 0.4× 8 0.2× 15 0.4× 2 408
R. Gusmeroli Italy 14 443 1.9× 97 0.7× 79 1.2× 41 0.8× 153 4.0× 33 622

Countries citing papers authored by Ádám Rák

Since Specialization
Citations

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

Fields of papers citing papers by Ádám Rák

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ádám Rák

This figure shows the co-authorship network connecting the top 25 collaborators of Ádám Rák. A scholar is included among the top collaborators of Ádám Rák 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 Ádám Rák. Ádám Rák is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Rák, Ádám, et al.. (2020). Towards chemically accurate QM/MM simulations on GPUs. Journal of Molecular Graphics and Modelling. 96. 107536–107536. 2 indexed citations
2.
Rák, Ádám, et al.. (2019). Classical molecular dynamics on graphics processing unit architectures. Wiley Interdisciplinary Reviews Computational Molecular Science. 10(2). 13 indexed citations
3.
Tornai, Gábor János, et al.. (2019). Calculation of Quantum Chemical Two-Electron Integrals by Applying Compiler Technology on GPU. Journal of Chemical Theory and Computation. 15(10). 5319–5331. 42 indexed citations
4.
Rák, Ádám, et al.. (2019). Robust Memristor Networks for Neuromorphic Computation Applications. Materials. 12(21). 3573–3573. 7 indexed citations
5.
Rák, Ádám, et al.. (2019). Optimized GPU implementation of Merck Molecular Force Field and Universal Force Field. Journal of Molecular Structure. 1188. 227–233. 29 indexed citations
6.
7.
Rák, Ádám & György Cserey. (2015). The BRUSH algorithm for two-electron integrals on GPU. Chemical Physics Letters. 622. 92–98. 29 indexed citations
8.
Rák, Ádám & György Cserey. (2014). Independent component analysis by memristor based neural networks. 1–2. 2 indexed citations
9.
Rák, Ádám & György Cserey. (2013). Emulation of analog memristors using low yield digital switching memristors. 18. 1–4. 1 indexed citations
10.
Rák, Ádám, et al.. (2010). CHUA'S CIRCUIT TOPOLOGY EVOLUTION USING GENETIC ALGORITHM. International Journal of Bifurcation and Chaos. 20(3). 687–696.
11.
Rák, Ádám, et al.. (2010). Cellular neural networks with memristive cell devices. ePrints Soton (University of Southampton). 938–941. 2 indexed citations
12.
Rák, Ádám & György Cserey. (2010). Macromodeling of the Memristor in SPICE. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 29(4). 632–636. 201 indexed citations
13.
Rák, Ádám, et al.. (2009). GPU Boosted CNN Simulator Library for Graphical Flow-Based Programmability. EURASIP Journal on Advances in Signal Processing. 2009(1). 3 indexed citations
14.
Rák, Ádám, et al.. (2008). Stochastic bitstream‐based CNN and its implementation on FPGA. International Journal of Circuit Theory and Applications. 37(4). 587–612. 13 indexed citations
15.
Rák, Ádám, et al.. (2008). GPU powered CNN simulator (SIMCNN) with graphical flow based programmability. 23. 163–168. 10 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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