Taesu Kim

857 total citations
33 papers, 588 citations indexed

About

Taesu Kim is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Computer Vision and Pattern Recognition. According to data from OpenAlex, Taesu Kim has authored 33 papers receiving a total of 588 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Electrical and Electronic Engineering, 10 papers in Hardware and Architecture and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Taesu Kim's work include Advanced Memory and Neural Computing (9 papers), Advanced Neural Network Applications (7 papers) and Ferroelectric and Negative Capacitance Devices (6 papers). Taesu Kim is often cited by papers focused on Advanced Memory and Neural Computing (9 papers), Advanced Neural Network Applications (7 papers) and Ferroelectric and Negative Capacitance Devices (6 papers). Taesu Kim collaborates with scholars based in South Korea, United States and Spain. Taesu Kim's co-authors include Jae‐Joon Kim, Hyungjun Kim, Alexander V. Veidenbaum, Rosario Cammarota, Mateo Valero, Yulhwa Kim, Jeonghwan Song, Seokjae Lim, Changhyuck Sung and Seunghyun Yoo and has published in prestigious journals such as IEEE Journal of Solid-State Circuits, Nanotechnology and Japanese Journal of Applied Physics.

In The Last Decade

Taesu Kim

27 papers receiving 565 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Taesu Kim South Korea 11 326 170 167 149 85 33 588
Sai Rahul Chalamalasetti United States 10 370 1.1× 118 0.7× 202 1.2× 178 1.2× 48 0.6× 32 587
Hongyang Jia China 11 668 2.0× 218 1.3× 157 0.9× 91 0.6× 33 0.4× 36 826
Richard Linderman United States 10 387 1.2× 132 0.8× 74 0.4× 84 0.6× 158 1.9× 43 574
Xiaoxin Cui China 11 473 1.5× 134 0.8× 106 0.6× 49 0.3× 87 1.0× 134 577
Naghmeh Karimi United States 14 517 1.6× 168 1.0× 476 2.9× 141 0.9× 103 1.2× 77 730
Hossam A. H. Fahmy Egypt 14 676 2.1× 73 0.4× 101 0.6× 56 0.4× 281 3.3× 63 869
Mohammad Nasim Imtiaz Khan United States 12 419 1.3× 216 1.3× 161 1.0× 471 3.2× 25 0.3× 44 801
En-Yu Yang United States 8 494 1.5× 151 0.9× 91 0.5× 58 0.4× 59 0.7× 15 620
Pi-Feng Chiu United States 14 574 1.8× 51 0.3× 174 1.0× 82 0.6× 68 0.8× 31 666
Sujan K. Gonugondla United States 13 640 2.0× 165 1.0× 140 0.8× 72 0.5× 49 0.6× 25 737

Countries citing papers authored by Taesu Kim

Since Specialization
Citations

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

Fields of papers citing papers by Taesu Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taesu Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Taesu Kim. A scholar is included among the top collaborators of Taesu Kim 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 Taesu Kim. Taesu Kim 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.
Kim, Taesu, et al.. (2025). Debunking the CUDA Myth Towards GPU-based AI Systems. 1760–1776.
2.
Kim, Hyungjun, et al.. (2022). BitBlade: Energy-Efficient Variable Bit-Precision Hardware Accelerator for Quantized Neural Networks. IEEE Journal of Solid-State Circuits. 57(6). 1924–1935. 35 indexed citations
3.
Kim, Taesu, et al.. (2022). Text-driven Emotional Style Control and Cross-speaker Style Transfer in Neural TTS. Interspeech 2022. 2313–2317. 7 indexed citations
4.
Kim, Yulhwa, et al.. (2020). Time-step interleaved weight reuse for LSTM neural network computing. 13–18. 6 indexed citations
5.
Kim, Taesu, et al.. (2020). V-LSTM: An Efficient LSTM Accelerator Using Fixed Nonzero-Ratio Viterbi-Based Pruning. 326–326. 2 indexed citations
6.
Kim, Taesu, et al.. (2019). Robust and Fine-grained Prosody Control of End-to-end Speech Synthesis. 5911–5915. 85 indexed citations
7.
Lee, Dongsoo, et al.. (2018). Viterbi-based Pruning for Sparse Matrix with Fixed and High Index Compression Ratio. Open Access System for Information Sharing (Pohang University of Science and Technology). 4 indexed citations
8.
Lee, Dongsoo, et al.. (2018). Double Viterbi: Weight Encoding for High Compression Ratio and Fast On-Chip Reconstruction for Deep Neural Network. Open Access System for Information Sharing (Pohang University of Science and Technology). 4 indexed citations
9.
Lim, Seokjae, Changhyuck Sung, Hyungjun Kim, et al.. (2018). Improved Synapse Device With MLC and Conductance Linearity Using Quantized Conduction for Neuromorphic Systems. IEEE Electron Device Letters. 39(2). 312–315. 61 indexed citations
10.
Sung, Changhyuck, Seokjae Lim, Hyungjun Kim, et al.. (2018). Effect of conductance linearity and multi-level cell characteristics of TaOx-based synapse device on pattern recognition accuracy of neuromorphic system. Nanotechnology. 29(11). 115203–115203. 35 indexed citations
11.
Kim, Taesu, et al.. (2018). Efficient Synapse Memory Structure for Reconfigurable Digital Neuromorphic Hardware. Frontiers in Neuroscience. 12. 829–829. 15 indexed citations
12.
Kim, Taesu, et al.. (2017). Input Voltage Mapping Optimized for Resistive Memory-Based Deep Neural Network Hardware. IEEE Electron Device Letters. 38(9). 1228–1231. 42 indexed citations
13.
Kim, Hong Bae, et al.. (2017). Analysis of Minimum Penetrated Depth of Pile bent of IPM Bridge. Journal of the Korean geoenvironmental society. 18(5). 45–53.
14.
Kim, Taesu, et al.. (2014). Multiple stream tracker. 1–10. 6 indexed citations
15.
Kim, Taesu, et al.. (2008). High-Speed Search Mechanism based on B-Tree Index Vector for Huge Web Log Mining and Web Attack Detection. Journal of Korea Multimedia Society. 11(11). 1601–1614. 1 indexed citations
16.
Kim, Hwi, et al.. (2005). Diffractive optical elements for shaping Gaussian Schell-model beams. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5636. 431–431. 1 indexed citations
17.
Kim, Taesu, et al.. (2005). Photopolymer-based demultiplexers with Superposed holographic gratings. IEEE Photonics Technology Letters. 17(3). 618–620. 6 indexed citations
18.
Chung, Seunghwan, et al.. (2005). Optical Cyclic Wavelength Shifter Using a Dual-Band Polymer Holographic Grating. Japanese Journal of Applied Physics. 44(9R). 6587–6587. 5 indexed citations
19.
Kim, Taesu, et al.. (2004). Mesh Watermarking Using POCS. ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications. 946–949. 1 indexed citations
20.
Kim, Taesu, et al.. (2002). Multispectral Image Data Compression Using Classified Prediction and KLT in Wavelet Transform Domain. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 86(6). 1492–1497. 1 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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2026