Sae Franklin

1.1k total citations · 1 hit paper
22 papers, 806 citations indexed

About

Sae Franklin is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Social Psychology. According to data from OpenAlex, Sae Franklin has authored 22 papers receiving a total of 806 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cognitive Neuroscience, 14 papers in Biomedical Engineering and 5 papers in Social Psychology. Recurrent topics in Sae Franklin's work include Motor Control and Adaptation (17 papers), Muscle activation and electromyography studies (13 papers) and Tactile and Sensory Interactions (7 papers). Sae Franklin is often cited by papers focused on Motor Control and Adaptation (17 papers), Muscle activation and electromyography studies (13 papers) and Tactile and Sensory Interactions (7 papers). Sae Franklin collaborates with scholars based in Germany, United Kingdom and Sweden. Sae Franklin's co-authors include David W. Franklin, Raz Leib, Daniel M. Wolpert, Faezeh Arab Hassani, Sunghoon Lee, Md Osman Goni Nayeem, Yan Wang, Gordon Cheng, Tomoyuki Yokota and Takao Someya and has published in prestigious journals such as Science, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Sae Franklin

20 papers receiving 788 citations

Hit Papers

Nanomesh pressure sensor for monitoring finger manipulati... 2020 2026 2022 2024 2020 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sae Franklin Germany 8 663 456 193 169 74 22 806
Raz Leib Germany 10 587 0.9× 391 0.9× 193 1.0× 198 1.2× 25 0.3× 26 741
Jan T. Meyer Switzerland 11 581 0.9× 195 0.4× 125 0.6× 107 0.6× 78 1.1× 17 781
Danilo Emilio De Rossi Italy 12 948 1.4× 195 0.4× 162 0.8× 133 0.8× 49 0.7× 37 1.3k
Yiyue Luo United States 12 576 0.9× 281 0.6× 134 0.7× 161 1.0× 29 0.4× 35 901
Wenzheng Heng United States 10 887 1.3× 254 0.6× 237 1.2× 299 1.8× 15 0.2× 16 1.1k
Florian L. Haufe Switzerland 10 604 0.9× 158 0.3× 96 0.5× 56 0.3× 8 0.1× 18 706
Rachel Gehlhar United States 6 554 0.8× 144 0.3× 168 0.9× 193 1.1× 5 0.1× 8 652
Sung-Phil Kim South Korea 9 275 0.4× 341 0.7× 61 0.3× 124 0.7× 24 0.3× 16 534
Luke E. Osborn United States 16 655 1.0× 593 1.3× 61 0.3× 157 0.9× 16 0.2× 46 950
Wen‐Hao Hsu Taiwan 15 649 1.0× 243 0.5× 203 1.1× 252 1.5× 4 0.1× 37 1.1k

Countries citing papers authored by Sae Franklin

Since Specialization
Citations

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

Fields of papers citing papers by Sae Franklin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sae Franklin

This figure shows the co-authorship network connecting the top 25 collaborators of Sae Franklin. A scholar is included among the top collaborators of Sae Franklin 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 Sae Franklin. Sae Franklin 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.
Howard, Ian S., Sae Franklin, & David W. Franklin. (2024). Kernels of Motor Memory Formation: Temporal Generalization in Bimanual Adaptation. Journal of Neuroscience. 44(47). e0359242024–e0359242024.
2.
Franklin, Sae, Raz Leib, Michael Dimitriou, & David W. Franklin. (2023). Congruent visual cues speed dynamic motor adaptation. Journal of Neurophysiology. 130(2). 319–331. 2 indexed citations
3.
Franklin, Sae, et al.. (2023). Goal‐directed modulation of stretch reflex gains is reduced in the non‐dominant upper limb. European Journal of Neuroscience. 58(9). 3981–4001. 2 indexed citations
4.
Franklin, Sae, et al.. (2023). Assistive Loading Promotes Goal-Directed Tuning of Stretch Reflex Gains. eNeuro. 10(2). ENEURO.0438–22.2023. 5 indexed citations
5.
Franklin, Sae & David W. Franklin. (2023). Visuomotor feedback tuning in the absence of visual error information. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 2 indexed citations
6.
Izadi, Mohammad, Sae Franklin, Marianna Bellafiore, & David W. Franklin. (2022). Motor Learning in Response to Different Experimental Pain Models Among Healthy Individuals: A Systematic Review. Frontiers in Human Neuroscience. 16. 863741–863741. 4 indexed citations
7.
Leib, Raz, et al.. (2022). Stability of inverted pendulum reveals transition between predictive control and impedance control in grip force modulation. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2019. 1481–1484.
8.
Lee, Sunghoon, Sae Franklin, Faezeh Arab Hassani, et al.. (2020). Nanomesh pressure sensor for monitoring finger manipulation without sensory interference. Science. 370(6519). 966–970. 524 indexed citations breakdown →
9.
Howard, Ian S., Sae Franklin, & David W. Franklin. (2020). Asymmetry in kinematic generalization between visual and passive lead-in movements are consistent with a forward model in the sensorimotor system. PLoS ONE. 15(1). e0228083–e0228083. 13 indexed citations
10.
Franklin, Sae, et al.. (2019). Feedback Delay Changes the Control of an Inverted Pendulum. PubMed. 2019. 1517–1520. 7 indexed citations
11.
Leib, Raz, et al.. (2019). LQG framework explains performance of balancing inverted pendulum with incongruent visual feedback. PubMed. 16. 1940–1943. 1 indexed citations
12.
Franklin, Sae, et al.. (2018). A Simulated Inverted Pendulum to Investigate Human Sensorimotor Control. PubMed. 414. 5166–5169. 6 indexed citations
13.
Franklin, Sae, et al.. (2018). Influence of Visual Feedback on the Sensorimotor Control of an Inverted Pendulum. PubMed. 414. 5170–5173. 7 indexed citations
14.
Franklin, Sae, Daniel M. Wolpert, & David W. Franklin. (2017). Rapid visuomotor feedback gains are tuned to the task dynamics. Journal of Neurophysiology. 118(5). 2711–2726. 26 indexed citations
15.
Franklin, David W., Alexandra Reichenbach, Sae Franklin, & Jörn Diedrichsen. (2016). Temporal Evolution of Spatial Computations for Visuomotor Control. Journal of Neuroscience. 36(8). 2329–2341. 40 indexed citations
16.
Franklin, David W., Sae Franklin, & Daniel M. Wolpert. (2014). Fractionation of the visuomotor feedback response to directions of movement and perturbation. Journal of Neurophysiology. 112(9). 2218–2233. 26 indexed citations
17.
Franklin, David W., Luc P. J. Selen, Sae Franklin, & Daniel M. Wolpert. (2013). Selection and control of limb posture for stability. PubMed. 2013. 5626–5629. 8 indexed citations
18.
Franklin, Sae, Daniel M. Wolpert, & David W. Franklin. (2012). Visuomotor feedback gains upregulate during the learning of novel dynamics. Journal of Neurophysiology. 108(2). 467–478. 105 indexed citations
19.
Franklin, Sae, et al.. (1981). Robust Flight Control: A Design Example. Journal of Guidance and Control. 4(5). 597–605. 23 indexed citations
20.
Franklin, Sae, et al.. (1980). Parameter Space Techniques for Robust Control System Design. Defense Technical Information Center (DTIC). 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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