Vihar Georgiev

2.0k total citations
157 papers, 1.4k citations indexed

About

Vihar Georgiev is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Materials Chemistry. According to data from OpenAlex, Vihar Georgiev has authored 157 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 126 papers in Electrical and Electronic Engineering, 45 papers in Biomedical Engineering and 34 papers in Materials Chemistry. Recurrent topics in Vihar Georgiev's work include Semiconductor materials and devices (88 papers), Advancements in Semiconductor Devices and Circuit Design (81 papers) and Nanowire Synthesis and Applications (39 papers). Vihar Georgiev is often cited by papers focused on Semiconductor materials and devices (88 papers), Advancements in Semiconductor Devices and Circuit Design (81 papers) and Nanowire Synthesis and Applications (39 papers). Vihar Georgiev collaborates with scholars based in United Kingdom, China and India. Vihar Georgiev's co-authors include Asen Asenov, John E. McGrady, Hamilton Carrillo-Nuñez, Laia Vilà‐Nadal, Leroy Cronin, Christoph Busche, Fikru Adamu-Lema, Cristina Medina-Bailón, Douglas J. Paul and Muhammad Mirza and has published in prestigious journals such as Nature, Journal of the American Chemical Society and SHILAP Revista de lepidopterología.

In The Last Decade

Vihar Georgiev

136 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vihar Georgiev United Kingdom 17 898 523 272 222 152 157 1.4k
Quan Liu China 22 446 0.5× 859 1.6× 287 1.1× 157 0.7× 124 0.8× 81 1.5k
Farman Ullah Pakistan 21 437 0.5× 600 1.1× 200 0.7× 118 0.5× 93 0.6× 66 1.2k
Rafi Shikler Israel 26 785 0.9× 755 1.4× 337 1.2× 92 0.4× 525 3.5× 60 1.7k
Anton Grigoriev Sweden 20 838 0.9× 753 1.4× 288 1.1× 44 0.2× 238 1.6× 49 1.4k
Yajing Sun China 23 822 0.9× 1.1k 2.1× 183 0.7× 62 0.3× 79 0.5× 95 1.7k
Sinan Li China 16 429 0.5× 447 0.9× 165 0.6× 79 0.4× 72 0.5× 42 1.0k
Prasanta Kumar Datta India 18 578 0.6× 485 0.9× 207 0.8× 42 0.2× 320 2.1× 111 1.1k
Zitong Wu China 22 395 0.4× 990 1.9× 326 1.2× 112 0.5× 34 0.2× 47 1.5k
Kyoung-Soo Kim South Korea 12 357 0.4× 799 1.5× 596 2.2× 210 0.9× 58 0.4× 55 1.3k
Ming Cheng China 15 317 0.4× 364 0.7× 168 0.6× 79 0.4× 61 0.4× 44 868

Countries citing papers authored by Vihar Georgiev

Since Specialization
Citations

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

Fields of papers citing papers by Vihar Georgiev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vihar Georgiev

This figure shows the co-authorship network connecting the top 25 collaborators of Vihar Georgiev. A scholar is included among the top collaborators of Vihar Georgiev 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 Vihar Georgiev. Vihar Georgiev 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.
Acharyya, Amit, et al.. (2025). Design Methodologies for Skyrmion-Based Circuits and Systems in AI-Driven Applications: Bi-Directional Integration [Feature]. IEEE Circuits and Systems Magazine. 25(3). 30–55.
2.
3.
Kumar, Naveen, et al.. (2025). A Hybrid Analytical and Machine Learning Model of BioFETs for the Detection of Peptides. IEEE Sensors Letters. 9(10). 1–4.
4.
Kumar, Naveen, Ankit Dixit, Md. Hasan Raza Ansari, et al.. (2025). Assessment of ion-sensitivity of Si3N4 based feedback field effect transistor using snap-back characteristics. Solid-State Electronics. 229. 109159–109159.
5.
6.
Ansari, Md. Hasan Raza, Naveen Kumar, Vihar Georgiev, & Nazek El‐Atab. (2024). Energy-Efficient Vertically Stacked NSFET-Based CTM for Logic in-Memory Computing. 370–374. 1 indexed citations
7.
Aggarwal, Neeraj, Navjeet Bagga, Ankit Dixit, et al.. (2024). Demonstration and Optimization of Multi-Fin Dual Spacer FinFET for Reliable Sub-THz Frequency Operation. 25–29.
8.
Georgiev, Vihar, et al.. (2024). The study of electron mobility on ultra-scaled silicon nanosheet FET. Physica Scripta. 99(7). 75410–75410. 2 indexed citations
9.
Sengupta, Amretashis, et al.. (2024). Analysis of Random Discrete Dopants Embedded Nanowire Resonant Tunnelling Diodes for Generation of Physically Unclonable Functions. IEEE Transactions on Nanotechnology. 23. 815–821. 3 indexed citations
10.
Dutta, Tapas, et al.. (2023). Convolutional Machine Learning Method for Accelerating Nonequilibrium Green’s Function Simulations in Nanosheet Transistor. IEEE Transactions on Electron Devices. 70(10). 5448–5453. 8 indexed citations
11.
Chen, Lin, Jie Liang, Yuanqing Cheng, et al.. (2022). Carbon Nanotube SRAM in 5-nm Technology Node Design, Optimization, and Performance Evaluation—Part I: CNFET Transistor Optimization. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 30(4). 432–439. 20 indexed citations
12.
Chen, Lin, Jie Liang, Yuanqing Cheng, et al.. (2022). Carbon Nanotube SRAM in 5-nm Technology Node Design, Optimization, and Performance Evaluation—Part II: CNT Interconnect Optimization. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 30(4). 440–448. 6 indexed citations
13.
Zhang, J. F., James Brown, Zhigang Ji, et al.. (2022). An Integral Methodology for Predicting Long-Term RTN. IEEE Transactions on Electron Devices. 69(7). 3869–3875. 2 indexed citations
14.
Medina-Bailón, Cristina, Tapas Dutta, Daniel Nagy, et al.. (2021). Simulation and Modeling of Novel Electronic Device Architectures with NESS (Nano-Electronic Simulation Software): A Modular Nano TCAD Simulation Framework. Micromachines. 12(6). 680–680. 11 indexed citations
15.
Ding, Jie, et al.. (2021). KMC-based POM flash cell optimization and time-dependent performance investigation. Semiconductor Science and Technology. 36(7). 75021–75021.
16.
Sadi, Toufik, et al.. (2020). A Kinetic Monte Carlo Study of Retention Time in a POM Molecule-Based Flash Memory. IEEE Transactions on Nanotechnology. 19. 704–710. 6 indexed citations
17.
Medina-Bailón, Cristina, Hamilton Carrillo-Nuñez, Jaehyun Lee, et al.. (2020). Quantum Enhancement of a S/D Tunneling Model in a 2D MS-EMC Nanodevice Simulator: NEGF Comparison and Impact of Effective Mass Variation. Micromachines. 11(2). 204–204. 4 indexed citations
18.
Sadi, Toufik, Cristina Medina-Bailón, Mihail Nedjalkov, et al.. (2019). Simulation of the Impact of Ionized Impurity Scattering on the Total Mobility in Si Nanowire Transistors. Materials. 12(1). 124–124. 19 indexed citations
19.
Medina-Bailón, Cristina, J. L. Padilla, Toufik Sadi, et al.. (2019). Multisubband Ensemble Monte Carlo Analysis of Tunneling Leakage Mechanisms in Ultrascaled FDSOI, DGSOI, and FinFET Devices. IEEE Transactions on Electron Devices. 66(3). 1145–1152. 6 indexed citations
20.
Sadi, Toufik, et al.. (2019). Physical Insights into the Transport Properties of RRAMs Based on Transition Metal Oxides. Aaltodoc (Aalto University). 1–4. 2 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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