Torsten Lehmann

1.8k total citations
116 papers, 1.3k citations indexed

About

Torsten Lehmann is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Torsten Lehmann has authored 116 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Electrical and Electronic Engineering, 55 papers in Biomedical Engineering and 37 papers in Cellular and Molecular Neuroscience. Recurrent topics in Torsten Lehmann's work include Analog and Mixed-Signal Circuit Design (39 papers), Neuroscience and Neural Engineering (37 papers) and Advanced Memory and Neural Computing (34 papers). Torsten Lehmann is often cited by papers focused on Analog and Mixed-Signal Circuit Design (39 papers), Neuroscience and Neural Engineering (37 papers) and Advanced Memory and Neural Computing (34 papers). Torsten Lehmann collaborates with scholars based in Australia, Denmark and United Kingdom. Torsten Lehmann's co-authors include Yashodhan Moghe, Nigel H. Lovell, Gregg J. Suaning, Tim Piessens, Yuanyuan Yang, Tara Julia Hamilton, Kushal Das, Yan T. Wong, Andrew S. Dzurak and Robert G. Clark and has published in prestigious journals such as Optics Express, Sensors and IEEE Journal of Solid-State Circuits.

In The Last Decade

Torsten Lehmann

111 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
Torsten Lehmann Australia 18 1.0k 505 400 208 177 116 1.3k
Tony Tae-Hyoung Kim Singapore 22 1.5k 1.4× 265 0.5× 113 0.3× 90 0.4× 186 1.1× 154 1.7k
Qi Yu China 20 1.3k 1.3× 497 1.0× 417 1.0× 291 1.4× 235 1.3× 167 1.7k
Tony F. Wu United States 21 1.2k 1.1× 155 0.3× 154 0.4× 65 0.3× 186 1.1× 38 1.5k
Po-Chiun Huang Taiwan 20 744 0.7× 726 1.4× 78 0.2× 35 0.2× 17 0.1× 90 1.2k
Jawar Singh India 23 1.6k 1.5× 313 0.6× 78 0.2× 27 0.1× 95 0.5× 124 1.7k
Dongsuk Jeon South Korea 19 842 0.8× 292 0.6× 135 0.3× 124 0.6× 151 0.9× 58 1.2k
Leland Chang United States 23 2.7k 2.7× 356 0.7× 182 0.5× 140 0.7× 151 0.9× 47 2.9k
Shuenn-Yuh Lee Taiwan 25 1.2k 1.2× 1.2k 2.4× 377 0.9× 228 1.1× 50 0.3× 150 2.0k
Christos Papavassiliou United Kingdom 17 1.1k 1.1× 309 0.6× 472 1.2× 304 1.5× 79 0.4× 108 1.6k
Daniela De Venuto Italy 19 364 0.4× 394 0.8× 204 0.5× 257 1.2× 24 0.1× 121 935

Countries citing papers authored by Torsten Lehmann

Since Specialization
Citations

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

Fields of papers citing papers by Torsten Lehmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Torsten Lehmann

This figure shows the co-authorship network connecting the top 25 collaborators of Torsten Lehmann. A scholar is included among the top collaborators of Torsten Lehmann 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 Torsten Lehmann. Torsten Lehmann 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.
Lehmann, Torsten, et al.. (2023). Influence of V2O5 on the viscosity of heterogeneous basic oxygen furnace CaO-FeO-SiO2-MgO-V2O5-Al2O3-MnO-P2O5 slags. Journal of Non-Crystalline Solids. 616. 122468–122468. 8 indexed citations
2.
Wang, Han, Amr Al Abed, Leonardo Silvestri, et al.. (2023). A Bi-Directional Detection and Stimulation Optrode System With Charge Balancing for Neural Applications. Journal of Lightwave Technology. 41(13). 4463–4472. 1 indexed citations
3.
Ladouceur, François, Damia Mawad, Dorna Esrafilzadeh, et al.. (2023). Emerging trends in the development of flexible optrode arrays for electrophysiology. APL Bioengineering. 7(3). 31503–31503. 3 indexed citations
4.
Abed, Amr Al, Han Wang, Leonardo Silvestri, et al.. (2022). Liquid crystal electro-optical transducers for electrophysiology sensing applications. Journal of Neural Engineering. 19(5). 56031–56031. 7 indexed citations
5.
Lehmann, Torsten, et al.. (2018). A resistive DAC for a multi-stage sigma-delta modulator DAC with dynamic element matching. Analog Integrated Circuits and Signal Processing. 98(1). 109–123. 1 indexed citations
6.
Weste, Neil, et al.. (2016). Partial Dynamic Element Matching Technique for Digital-to-Analog Converters Used for Digital Harmonic-Cancelling Sine-Wave Synthesis. IEEE Transactions on Circuits and Systems I Regular Papers. 64(2). 296–309. 16 indexed citations
7.
Scheuerlein, H., et al.. (2012). New methods for clinical pathways—Business Process Modeling Notation (BPMN) and Tangible Business Process Modeling (t.BPM). Langenbeck s Archives of Surgery. 397(5). 755–761. 72 indexed citations
8.
Guenther, Thomas, et al.. (2011). Laser-micromachined, chip-scaled ceramic carriers for implantable neurostimulators. PubMed. 2011. 1085–1088. 2 indexed citations
9.
10.
Lehmann, Torsten, et al.. (2007). A Dual Band Wireless Power and FSK Data Telemetry for Biomedical Implants. Conference proceedings. 2007. 6596–6599. 33 indexed citations
11.
Kim, Chul, et al.. (2007). An UWB System and All-Digital Transmitter Architecture for Biotelemetry Systems. 대한전자공학회 ISOCC. 287–290. 1 indexed citations
12.
Lehmann, Torsten, et al.. (2007). Electrically evoked compound action potential (ECAP) stimulus-artefact (SA) blanking low-power low-noise CMOS amplifier. Conference proceedings. 41–44. 2 indexed citations
13.
Kim, Chul, Torsten Lehmann, & Saeid Nooshabadi. (2007). An ultra-wideband transceiver for biotelemetry systems. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6798. 67980A–67980A. 1 indexed citations
14.
Wong, Yan T., et al.. (2006). Microelectronic Retinal Prosthesis: II. Use of High-Voltage CMOS in Retinal Neurostimulators. PubMed. 121. 4651–4654. 11 indexed citations
15.
Wong, Yan T., et al.. (2006). The Design and Testing of an Epi-Retinal Vision Prosthesis Neurostimulator Capable of Concurrent Parallel Stimulation. PubMed. 2006. 4700–4709. 8 indexed citations
16.
Wong, Yan T., et al.. (2006). Microelectronic Retinal Prosthesis: I. A Neurostimulator for the Concurrent Activation of Multiple Electrodes. PubMed. 2006. 4647–4650. 4 indexed citations
17.
Lehmann, Torsten, et al.. (2002). Integrating data converters for picoampere currents from electrochemical transducers. 5. 709–712. 27 indexed citations
18.
Lehmann, Torsten, et al.. (1999). Biologically-Inspired On-Chip Learning in Pulsed Neural Networks. Analog Integrated Circuits and Signal Processing. 18(2-3). 117–131. 7 indexed citations
19.
Hertz, John, Anders Krogh, B. Lautrup, & Torsten Lehmann. (1997). Nonlinear backpropagation: doing backpropagation without derivatives of the activation function. IEEE Transactions on Neural Networks. 8(6). 1321–1327. 16 indexed citations
20.
Lehmann, Torsten. (1993). A HARDWARE EFFICIENT CASCADABLE CHIP SET FOR ANN'S WITH ON-CHIP BACKPROPAGATION. International Journal of Neural Systems. 4(4). 351–358. 6 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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