Nikhil Krishnan

725 total citations
21 papers, 194 citations indexed

About

Nikhil Krishnan is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Nikhil Krishnan has authored 21 papers receiving a total of 194 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Artificial Intelligence. Recurrent topics in Nikhil Krishnan's work include Algorithms and Data Compression (3 papers), Bacteriophages and microbial interactions (2 papers) and Advanced Memory and Neural Computing (2 papers). Nikhil Krishnan is often cited by papers focused on Algorithms and Data Compression (3 papers), Bacteriophages and microbial interactions (2 papers) and Advanced Memory and Neural Computing (2 papers). Nikhil Krishnan collaborates with scholars based in United States, India and Canada. Nikhil Krishnan's co-authors include Focco van den Akker, Robert A. Bonomo, Nhu Q. Nguyen, Krisztina M. Papp‐Wallace, Jacob G. Scott, Laura J. Rojas, Nara Yoon, Chiara Romagnoli, N. Manjubaashini and Fabio Prati and has published in prestigious journals such as PLoS ONE, Antimicrobial Agents and Chemotherapy and Biosensors and Bioelectronics.

In The Last Decade

Nikhil Krishnan

17 papers receiving 193 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nikhil Krishnan United States	7	101	59	56	25	24	21	194
Yue Shi China	9	104 1.0×	36 0.6×	73 1.3×	30 1.2×	9 0.4×	17	266
Steven M. Crespo‐Carbone United States	9	71 0.7×	48 0.8×	132 2.4×	34 1.4×	41 1.7×	9	244
James K. L. Holt United Kingdom	4	59 0.6×	34 0.6×	128 2.3×	20 0.8×	22 0.9×	4	255
Zeyu Zhu United States	10	43 0.4×	23 0.4×	189 3.4×	23 0.9×	21 0.9×	19	327
Yu Qian China	9	168 1.7×	46 0.8×	40 0.7×	37 1.5×	17 0.7×	16	333
Lang Yang China	9	78 0.8×	18 0.3×	136 2.4×	22 0.9×	15 0.6×	19	247
Kyle D. Schneider United States	7	186 1.8×	125 2.1×	183 3.3×	77 3.1×	29 1.2×	8	356
Fanny Fontaine France	5	59 0.6×	23 0.4×	125 2.2×	10 0.4×	38 1.6×	9	190
Matthew S. Curtis United States	5	62 0.6×	18 0.3×	155 2.8×	31 1.2×	44 1.8×	6	362

Countries citing papers authored by Nikhil Krishnan

Since Specialization

Citations

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

Fields of papers citing papers by Nikhil Krishnan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nikhil Krishnan

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Yavarinasab, Adel, Nikhil Krishnan, Luis Ruiz Pestana, et al.. (2025). Electrogenic dynamics of biofilm formation: Correlation between genetic expression and electrochemical activity in Bacillus subtilis. Biosensors and Bioelectronics. 276. 117218–117218. 1 indexed citations

Krishnan, Nikhil, Joseph A. Knight, Carolina Tropini, Luis Ruiz Pestana, & Diana Fusco. (2025). The what, when, where, and why of wrinkly morphology in biofilms. 6(3).

Raneesh, B., Nebu George Thomas, P. K. Binsi, et al.. (2024). Catechin as a functional additive in electrospun PCL/gelatin/nHA nanocomposite fibers for tissue engineering applications. Journal of Applied Polymer Science. 142(1). 2 indexed citations

Gonzalez‐Libreros, Jaime, Chao Wang, Ali Khaloo, et al.. (2023). Influence of equipment, weather and personnel experience on the digitalization and damage detection of concrete bridges. ce/papers. 6(5). 996–1005. 1 indexed citations

Manjubaashini, N., et al.. (2023). Chitosan bioactive glass scaffolds for in vivo subcutaneous implantation, toxicity assessment, and diabetic wound healing upon animal model. International Journal of Biological Macromolecules. 256(Pt 1). 128291–128291. 21 indexed citations

Card, Kyle J., Lacy D. Chick, Nikhil Krishnan, et al.. (2022). A low-cost, open-source evolutionary bioreactor and its educational use. eLife. 11. 4 indexed citations

Yoon, Nara, Nikhil Krishnan, & Jacob G. Scott. (2021). Theoretical modeling of collaterally sensitive drug cycles: shaping heterogeneity to allow adaptive therapy. Journal of Mathematical Biology. 83(5). 47–47. 12 indexed citations

Krishnan, Nikhil, et al.. (2021). Attention guided complementary feature integration for latent image recovery from noisy/blurry pairs. 1–9.

Weaver, Davis T., Emily Dolson, Nikhil Krishnan, et al.. (2020). UV-C tower for point-of-care decontamination of filtering facepiece respirators. American Journal of Infection Control. 49(4). 424–429. 16 indexed citations

10.

Dolson, Emily & Nikhil Krishnan. (2020). Data and analysis for use of UV-C radiation in idle biosafety cabinets tosterilize personal protective equipment. Zenodo (CERN European Organization for Nuclear Research).

11.

Kumar, Vijay, et al.. (2018). Structural studies and molecular dynamics simulations suggest a processive mechanism of exolytic lytic transglycosylase from Campylobacter jejuni. PLoS ONE. 13(5). e0197136–e0197136. 8 indexed citations

12.

Krishnan, Nikhil, et al.. (2018). Synaptic efficacy shapes resource limitations in working memory. Journal of Computational Neuroscience. 44(3). 273–295. 8 indexed citations

13.

Krishnan, Nikhil & Zachary P. Kilpatrick. (2018). Optimizing a jump-diffusion model of a starving forager. Physical review. E. 98(5). 2 indexed citations

14.

Krishnan, Nikhil, et al.. (2017). Interacting bumps model of item limits in working memory.

15.

Nguyen, Nhu Q., Nikhil Krishnan, Laura J. Rojas, et al.. (2016). Crystal Structures of KPC-2 and SHV-1 β-Lactamases in Complex with the Boronic Acid Transition State Analog S02030. Antimicrobial Agents and Chemotherapy. 60(3). 1760–1766. 33 indexed citations

16.

Krishnan, Nikhil, Nhu Q. Nguyen, Krisztina M. Papp‐Wallace, Robert A. Bonomo, & Focco van den Akker. (2015). Inhibition of Klebsiella β-Lactamases (SHV-1 and KPC-2) by Avibactam: A Structural Study. PLoS ONE. 10(9). e0136813–e0136813. 71 indexed citations

17.

Krishnan, Nikhil & Dror Baron. (2015). A Universal Parallel Two-Pass MDL Context Tree Compression Algorithm. IEEE Journal of Selected Topics in Signal Processing. 9(4). 741–748. 3 indexed citations

18.

Krishnan, Nikhil, Dror Baron, & M. Kıvanç Mıhçak. (2014). A parallel two-pass MDL context tree algorithm for universal source coding. 1862–1866. 3 indexed citations

19.

Krishnan, Nikhil & Dror Baron. (2014). Performance of parallel two-pass MDL context tree algorithm. 331–335. 1 indexed citations

20.

Krishnan, Nikhil, et al.. (2011). Extensions to Orthogonal Matching Pursuit for Compressed Sensing. 24. 1–5. 4 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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