Ivan Dimov

3.1k total citations
145 papers, 1.3k citations indexed

About

Ivan Dimov is a scholar working on Numerical Analysis, Atomic and Molecular Physics, and Optics and Statistics, Probability and Uncertainty. According to data from OpenAlex, Ivan Dimov has authored 145 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Numerical Analysis, 33 papers in Atomic and Molecular Physics, and Optics and 22 papers in Statistics, Probability and Uncertainty. Recurrent topics in Ivan Dimov's work include Mathematical Approximation and Integration (30 papers), Probabilistic and Robust Engineering Design (21 papers) and Quantum and electron transport phenomena (20 papers). Ivan Dimov is often cited by papers focused on Mathematical Approximation and Integration (30 papers), Probabilistic and Robust Engineering Design (21 papers) and Quantum and electron transport phenomena (20 papers). Ivan Dimov collaborates with scholars based in Bulgaria, United Kingdom and Denmark. Ivan Dimov's co-authors include Zahari Zlatev, Jean Michel Sellier, Mihail Nedjalkov, Rayna Georgieva, Tzvetan Ostromsky, Krassimir Georgiev, István Faragó, S. Selberherr, Aneta Karaivanova and Vassil Alexandrov and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Applied Physics and Physical Review B.

In The Last Decade

Ivan Dimov

130 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ivan Dimov Bulgaria 19 315 271 201 189 180 145 1.3k
Stephen Nash United States 7 135 0.4× 328 1.2× 189 0.9× 483 2.6× 91 0.5× 12 1.7k
José Luis Morales Mexico 14 139 0.4× 232 0.9× 196 1.0× 267 1.4× 69 0.4× 25 1.6k
Martin Buhmann Germany 20 155 0.5× 379 1.4× 250 1.2× 316 1.7× 130 0.7× 61 2.5k
Ward Cheney United States 10 151 0.5× 314 1.2× 284 1.4× 329 1.7× 86 0.5× 14 2.2k
Gregory E. Fasshauer United States 25 190 0.6× 382 1.4× 293 1.5× 216 1.1× 113 0.6× 60 2.7k
Eric Phipps United States 15 98 0.3× 109 0.4× 139 0.7× 326 1.7× 341 1.9× 43 1.2k
Vicente Hernández Spain 18 263 0.8× 112 0.4× 312 1.6× 234 1.2× 39 0.2× 107 1.7k
Roscoe Bartlett United States 12 86 0.3× 169 0.6× 145 0.7× 281 1.5× 66 0.4× 25 1.4k
Stephen G. Nash United States 16 96 0.3× 505 1.9× 255 1.3× 577 3.1× 95 0.5× 33 2.1k
Fausto Saleri Italy 21 106 0.3× 378 1.4× 221 1.1× 314 1.7× 52 0.3× 62 1.8k

Countries citing papers authored by Ivan Dimov

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Dimov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Dimov

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Dimov. A scholar is included among the top collaborators of Ivan Dimov 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 Ivan Dimov. Ivan Dimov 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.
Ніценко, Віталій, et al.. (2024). FINANCIAL POTENTIAL FOR EXPANDING THE OPPORTUNITIES OF A SMALL ENTERPRISE UNDER THE CONDITIONS OF SUSTAINABLE DEVELOPMENT. SHILAP Revista de lepidopterología. 6(59). 261–272.
2.
Dimov, Ivan, et al.. (2024). Circular economy and digital technologies as drivers of sustainable development of the agricultural sector of the region in Ukrain. Cadernos de Educação Tecnologia e Sociedade. 17(se3). 287–297.
3.
Dimov, Ivan, et al.. (2023). Unveiling the Power of Stochastic Methods: Advancements in Air Pollution Sensitivity Analysis of the Digital Twin. Atmosphere. 14(7). 1078–1078. 11 indexed citations
4.
Ostromsky, Tzvetan, et al.. (2023). Sensitivity Study of a Large-scale Air Pollution Model on the Bulgarian Petascale Supercomputer Discoverer. SHILAP Revista de lepidopterología. 35. 1093–1100. 1 indexed citations
5.
6.
Dimov, Ivan, et al.. (2023). Optimizing Air Pollution Modeling with a Highly-Convergent Quasi-Monte Carlo Method: A Case Study on the UNI-DEM Framework. Mathematics. 11(13). 2919–2919. 3 indexed citations
7.
Dimov, Ivan, et al.. (2022). Advanced stochastic approaches for option pricing based on Sobol sequence. AIP conference proceedings. 2522. 110001–110001.
8.
Zlatev, Zahari, Ivan Dimov, István Faragó, Krassimir Georgiev, & Ágnes Havasi. (2016). Stability of the Richardson Extrapolation combined with some implicit Runge–Kutta methods. Journal of Computational and Applied Mathematics. 310. 224–240. 6 indexed citations
9.
Dimov, Ivan, Sylvain Maire, & Jean Michel Sellier. (2015). A new Walk on Equations Monte Carlo method for solving systems of linear algebraic equations. Applied Mathematical Modelling. 39(15). 4494–4510. 26 indexed citations
10.
Zlatev, Zahari, Krassimir Georgiev, & Ivan Dimov. (2014). Studying absolute stability properties of the Richardson Extrapolation combined with explicit Runge–Kutta methods. Computers & Mathematics with Applications. 67(12). 2294–2307. 16 indexed citations
11.
Dimov, Ivan, et al.. (2013). Numerical analysis and its applications : 5th International Conference, NAA 2012, Lozenetz, Bulgaria, June 15-20, 2012, revised selected papers. Springer eBooks. 1 indexed citations
12.
Dimov, Ivan, et al.. (2011). Numerical methods and applications : 8th International Conference, NMA 2014, Borovets, Bulgaria, August 20-24, 2014 : revised selected papers. CERN Document Server (European Organization for Nuclear Research). 2 indexed citations
13.
Dimov, Ivan, et al.. (2010). Studying the sensitivity of pollutants’ concentrations caused by variations of chemical rates. Journal of Computational and Applied Mathematics. 235(2). 391–402. 10 indexed citations
14.
Dimov, Ivan, et al.. (2007). What Monte Carlo models can do and cannot do efficiently?. Applied Mathematical Modelling. 32(8). 1477–1500. 20 indexed citations
15.
16.
Dimov, Ivan, István Faragó, & Zahari Zlatev. (2003). PARALLEL COMPUTATIONS WITH LARGE-SCALE AIR POLLUTION MODELS. The scientific electronic library of periodicals of the National Academy of Sciences of Ukraine (National Academy of Sciences of Ukraine). 1 indexed citations
17.
Dimov, Ivan, et al.. (1998). A new iterative Monte Carlo approach for inverse matrix problem. Journal of Computational and Applied Mathematics. 92(1). 15–35. 28 indexed citations
18.
Dimov, Ivan & Zahari Zlatev. (1997). Testing the Sensitivity of Air Pollution Levels to Variations of Some Chemical Rate Constants.. 11(2). 167–175. 11 indexed citations
19.
Nedjalkov, Mihail, Ivan Dimov, Fausto Rossi, & Carlo Jacoboni. (1996). Convergency of the Monte Carlo algorithm for the solution of the Wigner quantum-transport equation. Mathematical and Computer Modelling. 23(8-9). 159–166. 10 indexed citations
20.
Dimov, Ivan & Aneta Karaivanova. (1970). Monte Carlo Parallel Algorithms. WIT transactions on information and communication technologies. 3. 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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