Min Kim

545 total citations · 2 hit papers
10 papers, 447 citations indexed

About

Min Kim is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Control and Systems Engineering. According to data from OpenAlex, Min Kim has authored 10 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Biomedical Engineering, 4 papers in Cognitive Neuroscience and 2 papers in Control and Systems Engineering. Recurrent topics in Min Kim's work include Advanced Sensor and Energy Harvesting Materials (4 papers), Muscle activation and electromyography studies (3 papers) and Tactile and Sensory Interactions (3 papers). Min Kim is often cited by papers focused on Advanced Sensor and Energy Harvesting Materials (4 papers), Muscle activation and electromyography studies (3 papers) and Tactile and Sensory Interactions (3 papers). Min Kim collaborates with scholars based in South Korea, United States and Puerto Rico. Min Kim's co-authors include Sungho Jo, Kyun Kyu Kim, Seung Hwan Ko, Joonhwa Choi, Phillip Won, Inho Ha, Jaewon Kim, Samuel E. Root, Bao‐Nguyen T. Nguyen and JinKi Min and has published in prestigious journals such as Nature Communications, IEEE Transactions on Industrial Informatics and Transactions of the American Mathematical Society.

In The Last Decade

Min Kim

9 papers receiving 433 citations

Hit Papers

A deep-learned skin sensor decoding the epicentral human ... 2020 2026 2022 2024 2020 2022 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A deep-learned skin sensor decoding the epicentral human motions
    2020 243 citations Kyun Kyu Kim, Inho Ha et al. Nature Communications profile →
  2. A substrate-less nanomesh receptor with meta-learning for rapid hand task recognition
    2022 131 citations Kyun Kyu Kim, Min Kim et al. Nature Electronics profile →

Peers

Min Kim
Jacob Sacks United States
Yongsang Yoo South Korea
Jose Barreiros United States
Anzong Zheng United Kingdom
Weihao Zheng China
Yunzhao Bai China
Talha Agcayazi United States
Yun‐Soung Kim United States
Milan Raj United States
Jacob Sacks United States
Min Kim
Citations per year, relative to Min Kim Min Kim (= 1×) peers Jacob Sacks

Countries citing papers authored by Min Kim

Since Specialization
Citations

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

Fields of papers citing papers by Min Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Kim

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

All Works

10 of 10 papers shown
1.
Kim, Min, et al.. (2024). Multiple Hand Posture Rehabilitation System Using Vision-Based Intention Detection and Soft-Robotic Glove. IEEE Transactions on Industrial Informatics. 20(4). 6499–6509. 16 indexed citations
2.
Kim, Min, et al.. (2023). HybGrasp: A Hybrid Learning-to-Adapt Architecture for Efficient Robot Grasping. IEEE Robotics and Automation Letters. 8(12). 8390–8397.
3.
Kim, Kyun Kyu, Min Kim, Jin Kim, et al.. (2022). A substrate-less nanomesh receptor with meta-learning for rapid hand task recognition. Nature Electronics. 131 indexed citations breakdown →
4.
Kim, Min, Hyungmin Choi, Kyu‐Jin Cho, & Sungho Jo. (2021). Single to Multi: Data-Driven High Resolution Calibration Method for Piezoresistive Sensor Array. IEEE Robotics and Automation Letters. 6(3). 4970–4977. 15 indexed citations
5.
Kim, Kyun Kyu, Inho Ha, Min Kim, et al.. (2020). A deep-learned skin sensor decoding the epicentral human motions. Nature Communications. 11(1). 2149–2149. 243 indexed citations breakdown →
6.
Kim, Min, et al.. (2019). Semi-Supervised Gait Generation With Two Microfluidic Soft Sensors. IEEE Robotics and Automation Letters. 4(3). 2501–2507. 26 indexed citations
7.
8.
Kim, Min. (2006). Frankel’s theorem in the symplectic category. Transactions of the American Mathematical Society. 358(10). 4367–4377. 3 indexed citations
9.
Kim, Min, et al.. (2004). A parallel cell‐based DSMC method on unstructured adaptive meshes. International Journal for Numerical Methods in Fluids. 44(12). 1317–1335. 8 indexed citations
10.
Kim, Young-Sang, Bong‐Jin Yum, & Min Kim. (2002). A hybrid model of partial least squares and artificial neural network for analyzing process monitoring data. 3. 2292–2297. 3 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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