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.
Challenges and Outlook in Robotic Manipulation of Deformable Objects
2022159 citationsJihong Zhu, Andrea Cherubini et al.IEEE Robotics & Automation Magazineprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Michael Gienger
Since
Specialization
Citations
This map shows the geographic impact of Michael Gienger'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 Michael Gienger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Gienger more than expected).
This network shows the impact of papers produced by Michael Gienger. 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 Michael Gienger. The network helps show where Michael Gienger may publish in the future.
Co-authorship network of co-authors of Michael Gienger
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Gienger.
A scholar is included among the top collaborators of Michael Gienger 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 Michael Gienger. Michael Gienger is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhu, Jihong, Andrea Cherubini, Claire Dune, et al.. (2022). Challenges and Outlook in Robotic Manipulation of Deformable Objects. IEEE Robotics & Automation Magazine. 29(3). 67–77.159 indexed citations breakdown →
Gienger, Michael, et al.. (2020). Bayesian Domain Randomization for Sim-to-Real Transfer.. arXiv (Cornell University).6 indexed citations
12.
Stouraitis, Theodoros, et al.. (2018). Dyadic collaborative Manipulation through Hybrid Trajectory Optimization.. Edinburgh Research Explorer (University of Edinburgh). 869–878.7 indexed citations
Luksch, Tobias, Michael Gienger, Manuel Mühlig, & Takahide Yoshiike. (2012). A Dynamical Systems Approach to Adaptive Sequencing of Movement Primitives. 1–6.5 indexed citations
Gienger, Michael, et al.. (2010). Movement control in biologically plausible frames of reference. 1–7.2 indexed citations
19.
Pfeiffer, Friedrich, K. Löffler, Michael Gienger, & Heinz Ulbrich. (2004). SENSOR AND CONTROL ASPECTS OF BIPED ROBOT "JOHNNIE". International Journal of Humanoid Robotics. 1(3). 481–496.23 indexed citations
20.
Gienger, Michael. (2001). Design and sensor system of a biped robot. Medical Entomology and Zoology. 205–212.6 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.