Roman Genov

5.1k total citations
178 papers, 3.6k citations indexed

About

Roman Genov is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Biomedical Engineering. According to data from OpenAlex, Roman Genov has authored 178 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 112 papers in Electrical and Electronic Engineering, 93 papers in Cellular and Molecular Neuroscience and 82 papers in Biomedical Engineering. Recurrent topics in Roman Genov's work include Neuroscience and Neural Engineering (92 papers), Advanced Memory and Neural Computing (59 papers) and Analog and Mixed-Signal Circuit Design (57 papers). Roman Genov is often cited by papers focused on Neuroscience and Neural Engineering (92 papers), Advanced Memory and Neural Computing (59 papers) and Analog and Mixed-Signal Circuit Design (57 papers). Roman Genov collaborates with scholars based in Canada, United States and Australia. Roman Genov's co-authors include Karim Abdelhalim, José Luis Pérez Velázquez, Gert Cauwenberghs, Muhammad Tariqus Salam, Peter L. Carlen, Hamed Mazhab Jafari, Hossein Kassiri, Nima Soltani, M. Reza Pazhouhandeh and Arezu Bagheri and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Roman Genov

165 papers receiving 3.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roman Genov Canada 32 2.1k 1.9k 1.6k 1.2k 323 178 3.6k
Andreas Demosthenous United Kingdom 30 2.3k 1.1× 1.1k 0.6× 2.0k 1.2× 687 0.6× 152 0.5× 334 3.6k
Timothy G. Constandinou United Kingdom 28 1.3k 0.6× 1.4k 0.7× 950 0.6× 1.1k 0.9× 228 0.7× 216 2.6k
Stephen P. DeWeerth United States 28 984 0.5× 839 0.4× 1.1k 0.7× 701 0.6× 93 0.3× 133 2.3k
Refet Fırat Yazıcıoğlu Belgium 38 2.1k 1.0× 1.9k 1.0× 3.0k 1.9× 1.3k 1.1× 151 0.5× 95 4.5k
Eugenio Culurciello United States 30 2.2k 1.0× 776 0.4× 649 0.4× 588 0.5× 92 0.3× 125 3.4k
Wentai Liu United States 27 2.6k 1.2× 2.0k 1.0× 1.4k 0.9× 906 0.8× 24 0.1× 131 3.9k
Maurits Ortmanns Germany 27 2.8k 1.3× 962 0.5× 2.3k 1.4× 485 0.4× 112 0.3× 318 3.4k
Omid Kavehei Australia 30 2.5k 1.2× 894 0.5× 682 0.4× 1.0k 0.9× 33 0.1× 115 4.1k
Chung‐Yu Wu Taiwan 28 2.5k 1.2× 509 0.3× 964 0.6× 266 0.2× 88 0.3× 271 3.1k
C. Toumazou United Kingdom 35 3.7k 1.8× 859 0.4× 3.2k 2.0× 297 0.3× 468 1.4× 253 4.9k

Countries citing papers authored by Roman Genov

Since Specialization
Citations

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

Fields of papers citing papers by Roman Genov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roman Genov

This figure shows the co-authorship network connecting the top 25 collaborators of Roman Genov. A scholar is included among the top collaborators of Roman Genov 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 Roman Genov. Roman Genov 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.
Nag, Sudip, et al.. (2025). Energy-Efficient Adaptive Neural Stimulator With Waveform Prediction by Sub-Threshold Interrogation of the Electrode-Tissue Interface. IEEE Transactions on Biomedical Circuits and Systems. 19(6). 1142–1159.
2.
Chen, Brian S., et al.. (2024). SITU: Stochastic input encoding and weight update thresholding for efficient memristive neural network in-situ training. Neurocomputing. 605. 128275–128275. 1 indexed citations
3.
Walters, Ben, et al.. (2024). Advancing Image Classification with Phase-coded Ultra-Efficient Spiking Neural Networks. 33. 1–5. 2 indexed citations
4.
Genov, Roman, et al.. (2024). Closed-Loop Control of Functional Electrical Stimulation Using a Selectively Recording and Bidirectional Nerve Cuff Interface. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32. 504–513. 4 indexed citations
5.
Amirsoleimani, Amirali, et al.. (2023). WALLAX: A memristor-based Gaussian random number generator. Neurocomputing. 566. 126933–126933. 3 indexed citations
6.
Chen, Wenzheng, et al.. (2023). 39 000-Subexposures/s Dual-ADC CMOS Image Sensor With Dual-Tap Coded-Exposure Pixels for Single-Shot HDR and 3-D Computational Imaging. IEEE Journal of Solid-State Circuits. 58(11). 3150–3163. 5 indexed citations
7.
Xu, Jianxiong, Sudip Nag, Gerard O’Leary, et al.. (2023). Fascicle-Selective Ultrasound-Powered Bidirectional Wireless Peripheral Nerve Interface IC. IEEE Transactions on Biomedical Circuits and Systems. 17(6). 1237–1256. 11 indexed citations
8.
Genov, Roman, et al.. (2023). Resource-Efficient Neural Network Architectures for Classifying Nerve Cuff Recordings on Implantable Devices. IEEE Transactions on Biomedical Engineering. 71(2). 631–639. 4 indexed citations
9.
Genov, Roman, et al.. (2023). Efficient Memristive Stochastic Differential Equation Solver. SHILAP Revista de lepidopterología. 5(8). 3 indexed citations
10.
11.
Chen, Wenzheng, et al.. (2022). A 39,000 Subexposures/s CMOS Image Sensor with Dual-tap Coded-exposure Data-memory Pixel for Adaptive Single-shot Computational Imaging. 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits). 78–79. 5 indexed citations
12.
Amirsoleimani, Amirali, Jianxiong Xu, Fabien Alibart, et al.. (2022). CODEX: Stochastic Encoding Method to Relax Resistive Crossbar Accelerator Design Requirements. IEEE Transactions on Circuits & Systems II Express Briefs. 69(8). 3356–3360. 3 indexed citations
13.
Xu, Jianxiong, et al.. (2021). Bidirectional Peripheral Nerve Interface With 64 Second-Order Opamp-Less ΔΣ ADCs and Fully Integrated Wireless Power/Data Transmission. IEEE Journal of Solid-State Circuits. 56(11). 3247–3262. 35 indexed citations
14.
Amirsoleimani, Amirali, Fabien Alibart, Jianxiong Xu, et al.. (2020). In‐Memory Vector‐Matrix Multiplication in Monolithic Complementary Metal–Oxide–Semiconductor‐Memristor Integrated Circuits: Design Choices, Challenges, and Perspectives. SHILAP Revista de lepidopterología. 2(11). 141 indexed citations
15.
Kassiri, Hossein, Fu‐Der Chen, Muhammad Tariqus Salam, et al.. (2019). Arbitrary-Waveform Electro-Optical Intracranial Neurostimulator With Load-Adaptive High-Voltage Compliance. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27(4). 582–593. 14 indexed citations
16.
Stoppa, David, et al.. (2019). Dual-Tap Computational Photography Image Sensor With Per-Pixel Pipelined Digital Memory for Intra-Frame Coded Multi-Exposure. IEEE Journal of Solid-State Circuits. 54(11). 3191–3202. 7 indexed citations
17.
18.
Gulak, Glenn, et al.. (2018). Superresolution Line Scan Image Sensor for Multimodal Microscopy. IEEE Transactions on Biomedical Circuits and Systems. 12(5). 1165–1176. 3 indexed citations
19.
O’Leary, Gerard, M. Reza Pazhouhandeh, Michael Chang, et al.. (2018). A recursive-memory brain-state classifier with 32-channel track-and-zoom Δ2 Σ ADCs and Charge-Balanced Programmable Waveform Neurostimulators. 296–298. 27 indexed citations
20.
Genov, Roman, et al.. (2002). A 5.9mW 6.5GMACS CID/DRAM array processor. European Solid-State Circuits Conference. 715–718. 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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