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.
Analysis and Observations From the First Amazon Picking Challenge
Countries citing papers authored by Kostas E. Bekris
Since
Specialization
Citations
This map shows the geographic impact of Kostas E. Bekris'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 Kostas E. Bekris with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kostas E. Bekris more than expected).
Fields of papers citing papers by Kostas E. Bekris
This network shows the impact of papers produced by Kostas E. Bekris. 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 Kostas E. Bekris. The network helps show where Kostas E. Bekris may publish in the future.
Co-authorship network of co-authors of Kostas E. Bekris
This figure shows the co-authorship network connecting the top 25 collaborators of Kostas E. Bekris.
A scholar is included among the top collaborators of Kostas E. Bekris 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 Kostas E. Bekris. Kostas E. Bekris is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhu, Shaojun, Andrew Kimmel, Kostas E. Bekris, & Abdeslam Boularias. (2017). Model Identification via Physics Engines for Improved Policy Search.. arXiv (Cornell University).6 indexed citations
Krontiris, Athanasios, et al.. (2012). Towards using discrete multiagent pathfinding to address continuous problems. National Conference on Artificial Intelligence.4 indexed citations
Bekris, Kostas E., et al.. (2010). Fragile Watermarking of 3D Motion Data.. 111–116.1 indexed citations
18.
Bekris, Kostas E. & Lydia E. Kavraki. (2008). Informed and probabilistically complete search for motion planning under differential constraints. National Conference on Artificial Intelligence.12 indexed citations
Bekris, Kostas E., et al.. (2002). PYTHEAS: an Integrated Robotic System with Autonomous Navigation Capabilities. 8(2). 81–92.1 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.