Rico Jonschkowski

954 total citations
12 papers, 401 citations indexed

About

Rico Jonschkowski is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Rico Jonschkowski has authored 12 papers receiving a total of 401 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Control and Systems Engineering and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Rico Jonschkowski's work include Reinforcement Learning in Robotics (7 papers), Robot Manipulation and Learning (6 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Rico Jonschkowski is often cited by papers focused on Reinforcement Learning in Robotics (7 papers), Robot Manipulation and Learning (6 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Rico Jonschkowski collaborates with scholars based in Germany, United States and France. Rico Jonschkowski's co-authors include Oliver Brock, Roberto Martín-Martín, Clemens Eppner, Sebastian Höfer, Vincent Wall, Kurt Konolige, Anelia Angelova, Antonin Raffin, Freek Stulp and Yevgen Chebotar and has published in prestigious journals such as Autonomous Robots and elib (German Aerospace Center).

In The Last Decade

Rico Jonschkowski

12 papers receiving 371 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rico Jonschkowski Germany	8	233	173	125	112	79	12	401
Balakumar Sundaralingam United States	12	345 1.5×	206 1.2×	94 0.8×	107 1.0×	129 1.6×	17	482
Thomas Rühr Germany	9	168 0.7×	142 0.8×	89 0.7×	99 0.9×	48 0.6×	16	341
Ulrich Klank Germany	11	264 1.1×	288 1.7×	125 1.0×	169 1.5×	85 1.1×	17	573
Zhixing Xue Germany	11	309 1.3×	173 1.0×	91 0.7×	54 0.5×	149 1.9×	24	409
Daniel Kappler Germany	12	393 1.7×	198 1.1×	75 0.6×	168 1.5×	189 2.4×	20	555
Stephen James United Kingdom	9	210 0.9×	188 1.1×	95 0.8×	133 1.2×	35 0.4×	13	358
Alper Aydemir Sweden	10	130 0.6×	231 1.3×	159 1.3×	150 1.3×	68 0.9×	17	460
Hamidreza Kasaei Netherlands	13	199 0.9×	350 2.0×	150 1.2×	192 1.7×	56 0.7×	58	566
Fadri Furrer Switzerland	9	184 0.8×	176 1.0×	116 0.9×	61 0.5×	67 0.8×	12	353
Lars‐Peter Ellekilde Denmark	13	247 1.1×	121 0.7×	97 0.8×	44 0.4×	87 1.1×	36	388

Countries citing papers authored by Rico Jonschkowski

Since Specialization

Citations

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

Fields of papers citing papers by Rico Jonschkowski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rico Jonschkowski

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

All Works

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12 of 12 papers shown

1.

Kalashnikov, Dmitry, Yevgen Chebotar, Rico Jonschkowski, et al.. (2021). Scaling Up Multi-Task Robotic Reinforcement Learning. 3 indexed citations

2.

Jonschkowski, Rico, et al.. (2020). KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objects. 11599–11607. 79 indexed citations

3.

Jonschkowski, Rico, et al.. (2019). State Representation Learning with Robotic Priors for Partially Observable Environments. 6693–6699. 5 indexed citations

4.

Jonschkowski, Rico. (2018). Found by NEMO: Unsupervised Object Detection from Negative Examples and Motion. 1 indexed citations

5.

Eppner, Clemens, Sebastian Höfer, Rico Jonschkowski, et al.. (2018). Four aspects of building robotic systems: lessons from the Amazon Picking Challenge 2015. Autonomous Robots. 42(7). 1459–1475. 24 indexed citations

6.

Raffin, Antonin, Sebastian Höfer, Rico Jonschkowski, Oliver Brock, & Freek Stulp. (2017). Unsupervised Learning of State Representations for Multiple Tasks. elib (German Aerospace Center). 3 indexed citations

7.

Jonschkowski, Rico & Oliver Brock. (2017). End-to-End Learnable Histogram Filters. 10 indexed citations

8.

Eppner, Clemens, Sebastian Höfer, Rico Jonschkowski, et al.. (2017). Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems. 4831–4835. 38 indexed citations

9.

Eppner, Clemens, Sebastian Höfer, Rico Jonschkowski, et al.. (2016). Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems. 91 indexed citations

10.

Jonschkowski, Rico, Clemens Eppner, Sebastian Höfer, Roberto Martín-Martín, & Oliver Brock. (2016). Probabilistic multi-class segmentation for the Amazon Picking Challenge. 50 indexed citations

11.

Jonschkowski, Rico & Oliver Brock. (2015). Learning state representations with robotic priors. Autonomous Robots. 39(3). 407–428. 75 indexed citations

12.

Jonschkowski, Rico & Oliver Brock. (2014). State Representation Learning in Robotics: Using Prior Knowledge about Physical Interaction. 22 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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