Maxim Kalashnikov

640 total citations
16 papers, 510 citations indexed

About

Maxim Kalashnikov is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Biophysics. According to data from OpenAlex, Maxim Kalashnikov has authored 16 papers receiving a total of 510 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Biomedical Engineering, 8 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Biophysics. Recurrent topics in Maxim Kalashnikov's work include Optical Imaging and Spectroscopy Techniques (8 papers), Bacterial Identification and Susceptibility Testing (6 papers) and Spectroscopy Techniques in Biomedical and Chemical Research (6 papers). Maxim Kalashnikov is often cited by papers focused on Optical Imaging and Spectroscopy Techniques (8 papers), Bacterial Identification and Susceptibility Testing (6 papers) and Spectroscopy Techniques in Biomedical and Chemical Research (6 papers). Maxim Kalashnikov collaborates with scholars based in United States, Spain and Germany. Maxim Kalashnikov's co-authors include Michael S. Feld, Alexis F. Sauer-Budge, André Sharon, Vadim Backman, Adam Wax, Kamran Badizadegan, Jennifer Campbell, Christine McBeth, Venkatesh Gopal and Jean C. Lee and has published in prestigious journals such as Physical Review Letters, Scientific Reports and Optics Letters.

In The Last Decade

Maxim Kalashnikov

16 papers receiving 502 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Maxim Kalashnikov United States	10	374	147	120	82	65	16	510
Oleg Ryabchykov Germany	15	178 0.5×	404 2.7×	50 0.4×	73 0.9×	138 2.1×	30	603
Valery Patsekin United States	11	192 0.5×	214 1.5×	24 0.2×	42 0.5×	185 2.8×	30	452
Daniel Spencer United Kingdom	14	749 2.0×	47 0.3×	8 0.1×	63 0.8×	145 2.2×	24	898
Azeem Ahmad India	14	269 0.7×	185 1.3×	30 0.3×	20 0.2×	55 0.8×	64	559
Matthew A. Stott United States	14	427 1.1×	47 0.3×	15 0.1×	12 0.1×	159 2.4×	33	578
Christopher Rinaldi United Kingdom	12	96 0.3×	254 1.7×	35 0.3×	5 0.1×	170 2.6×	14	452
Kong‐Thon Tsen United States	11	98 0.3×	30 0.2×	34 0.3×	10 0.1×	60 0.9×	21	391
Changhe Huang United States	5	93 0.2×	248 1.7×	28 0.2×	10 0.1×	90 1.4×	5	327
J. Castro-Ramos Mexico	11	120 0.3×	90 0.6×	40 0.3×	7 0.1×	40 0.6×	44	298
Norbert Bergner Germany	12	168 0.4×	548 3.7×	77 0.6×	15 0.2×	183 2.8×	19	648

Countries citing papers authored by Maxim Kalashnikov

Since Specialization

Citations

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

Fields of papers citing papers by Maxim Kalashnikov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maxim Kalashnikov

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

All Works

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16 of 16 papers shown

1.

Kalashnikov, Maxim, Jean C. Lee, & Alexis F. Sauer-Budge. (2018). Optimization of Stress-Based Microfluidic Testing for Methicillin Resistance in Staphylococcus aureus Strains. Diagnostics. 8(2). 24–24. 3 indexed citations

2.

Kalashnikov, Maxim, Christine McBeth, Jean C. Lee, et al.. (2017). Rapid phenotypic stress-based microfluidic antibiotic susceptibility testing of Gram-negative clinical isolates. Scientific Reports. 7(1). 8031–8031. 31 indexed citations

3.

Fernández-Carballo, B. Leticia, Christine McBeth, Maxim Kalashnikov, et al.. (2017). Continuous-flow, microfluidic, qRT-PCR system for RNA virus detection. Analytical and Bioanalytical Chemistry. 410(1). 33–43. 41 indexed citations

4.

Fernández-Carballo, B. Leticia, Christine McBeth, Maxim Kalashnikov, et al.. (2016). Low-cost, real-time, continuous flow PCR system for pathogen detection. Biomedical Microdevices. 18(2). 34–34. 30 indexed citations

5.

Campbell, Jennifer, et al.. (2016). Microfluidic advances in phenotypic antibiotic susceptibility testing. Biomedical Microdevices. 18(6). 103–103. 30 indexed citations

6.

Kalashnikov, Maxim, Jennifer Campbell, Jean C. Lee, André Sharon, & Alexis F. Sauer-Budge. (2014). Stress-induced Antibiotic Susceptibility Testing on a Chip. Journal of Visualized Experiments. e50828–e50828. 5 indexed citations

7.

Kalashnikov, Maxim, Jennifer Campbell, Jean C. Lee, André Sharon, & Alexis F. Sauer-Budge. (2014). Stress-induced Antibiotic Susceptibility Testing on a Chip. Journal of Visualized Experiments. 1 indexed citations

8.

Kalashnikov, Maxim, Jean C. Lee, Jennifer Campbell, André Sharon, & Alexis F. Sauer-Budge. (2012). A microfluidic platform for rapid, stress-induced antibiotic susceptibility testing of Staphylococcus aureus. Lab on a Chip. 12(21). 4523–4523. 56 indexed citations

9.

Kalashnikov, Maxim, et al.. (2012). Assessing the contribution of cell body and intracellular organelles to the backward light scattering. Optics Express. 20(2). 816–816. 7 indexed citations

10.

Kalashnikov, Maxim, Wonshik Choi, Yongjin Sung, et al.. (2009). Assessing light scattering of intracellular organelles in single intact living cells. Optics Express. 17(22). 19674–19674. 27 indexed citations

11.

Hunter, Martin, Vadim Backman, Gabriel Popescu, et al.. (2006). Tissue Self-Affinity and Polarized Light Scattering in the Born Approximation: A New Model for Precancer Detection. Physical Review Letters. 97(13). 138102–138102. 101 indexed citations

12.

Lau, Condon, James W. Tunnell, Martin Hunter, et al.. (2006). Assessing epithelial cell nuclear morphology by using azimuthal light scattering spectroscopy. Optics Letters. 31(21). 3119–3119. 20 indexed citations

13.

Yu, Chung‐Chieh, Condon Lau, James W. Tunnell, et al.. (2006). Assessing Epithelial Cell Nuclear Morphology with Azimuthal Light Scattering Spectroscopy. Biomedical optics. 37. TuD2–TuD2. 1 indexed citations

14.

Wax, Adam, Changhuei Yang, Vadim Backman, et al.. (2002). Determination of particle size by using the angular distribution of backscattered light as measured with low-coherence interferometry. Journal of the Optical Society of America A. 19(4). 737–737. 53 indexed citations

15.

Backman, Vadim, Rajan Gurjar, Lev T. Perelman, et al.. (2002). <title>Imaging and measurement of cell structure and organization with submicron accuracy using light scattering spectroscopy</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4613. 101–110. 9 indexed citations

16.

Backman, Vadim, Venkatesh Gopal, Maxim Kalashnikov, et al.. (2001). Measuring cellular structure at submicrometer scale with light scattering spectroscopy. IEEE Journal of Selected Topics in Quantum Electronics. 7(6). 887–893. 95 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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