Julian Ibarz

9.7k total citations · 1 hit paper
11 papers, 635 citations indexed

About

Julian Ibarz is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Julian Ibarz has authored 11 papers receiving a total of 635 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Control and Systems Engineering and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Julian Ibarz's work include Reinforcement Learning in Robotics (7 papers), Robot Manipulation and Learning (5 papers) and Multimodal Machine Learning Applications (2 papers). Julian Ibarz is often cited by papers focused on Reinforcement Learning in Robotics (7 papers), Robot Manipulation and Learning (5 papers) and Multimodal Machine Learning Applications (2 papers). Julian Ibarz collaborates with scholars based in United States and Germany. Julian Ibarz's co-authors include Sergey Levine, Chelsea Finn, Peter Pástor, Mrinal Kalakrishnan, Jie Tan, Alex Irpan, Kanishka Rao, Mohi Khansari, C.J. Harris and Brijen Thananjeyan and has published in prestigious journals such as The International Journal of Robotics Research, IEEE Robotics and Automation Letters and IEEE Transactions on Information Technology in Biomedicine.

In The Last Decade

Julian Ibarz

11 papers receiving 619 citations

Hit Papers

1 papers align trajectories

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.

How to train your robot with deep reinforcement learning: lessons we have learned

2021 323 citations Julian Ibarz, Jie Tan et al. The International Journal of Robotics Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Julian Ibarz United States	6	337	318	142	139	66	11	635
Ahmed Hussein United Kingdom	3	219 0.6×	301 0.9×	166 1.2×	64 0.5×	83 1.3×	4	618
Nolan Wagener United States	4	278 0.8×	190 0.6×	109 0.8×	85 0.6×	74 1.1×	5	468
Abdeslam Boularias United States	16	392 1.2×	377 1.2×	253 1.8×	164 1.2×	36 0.5×	59	782
Antonin Raffin Germany	4	221 0.7×	286 0.9×	118 0.8×	71 0.5×	94 1.4×	9	758
Joni Pajarinen Finland	13	374 1.1×	391 1.2×	240 1.7×	94 0.7×	52 0.8×	52	875
Steven Bohez Belgium	13	211 0.6×	321 1.0×	199 1.4×	217 1.6×	34 0.5×	26	749
Danijar Hafner United States	8	188 0.6×	298 0.9×	136 1.0×	202 1.5×	42 0.6×	15	607
Yunfei Bai United States	10	360 1.1×	278 0.9×	229 1.6×	292 2.1×	36 0.5×	20	731
Katharina Mülling Germany	9	526 1.6×	486 1.5×	219 1.5×	191 1.4×	33 0.5×	13	869
Erwin Coumans United States	8	299 0.9×	255 0.8×	213 1.5×	281 2.0×	33 0.5×	13	697

Countries citing papers authored by Julian Ibarz

Since Specialization

Citations

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

Fields of papers citing papers by Julian Ibarz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julian Ibarz

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

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Ryoo, Michael S., Keerthana Gopalakrishnan, Ted Xiao, et al.. (2023). Token Turing Machines. 19070–19081. 4 indexed citations

2.

Thananjeyan, Brijen, Ashwin Balakrishna, Suraj Nair, et al.. (2021). Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones. IEEE Robotics and Automation Letters. 6(3). 4915–4922. 108 indexed citations

3.

Ibarz, Julian, Jie Tan, Chelsea Finn, et al.. (2021). How to train your robot with deep reinforcement learning: lessons we have learned. The International Journal of Robotics Research. 40(4-5). 698–721. 323 indexed citations breakdown →

4.

Rao, Kanishka, C.J. Harris, Alex Irpan, et al.. (2020). RL-CycleGAN: Reinforcement Learning Aware Simulation-to-Real. 11154–11163. 83 indexed citations

5.

Xiao, Ted, Eric Jang, Dmitry Kalashnikov, et al.. (2020). Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. arXiv (Cornell University). 1 indexed citations

6.

Rao, Kanishka, et al.. (2019). Off-Policy Evaluation via Off-Policy Classification. arXiv (Cornell University). 32. 5437–5448. 2 indexed citations

7.

Kalashnikov, Dmitry, Alex Irpan, Peter Pástor, et al.. (2018). QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation. 651–673. 71 indexed citations

8.

Eysenbach, Benjamin, Shixiang Gu, Julian Ibarz, & Sergey Levine. (2018). Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. MPG.PuRe (Max Planck Society). 26 indexed citations

9.

Jang, Eric, et al.. (2017). End-to-End Learning of Semantic Grasping. 119–132. 13 indexed citations

10.

Yatziv, Liron, Julian Ibarz, Norbert Strobel, Sourav Datta, & Guillermo Sapiro. (2011). Esophagus Silhouette Extraction and Reconstruction From Fluoroscopic Views for Cardiac Ablation Procedure Guidance. IEEE Transactions on Information Technology in Biomedicine. 15(5). 703–708. 1 indexed citations

11.

Abraira, Víctor & Julian Ibarz. (1986). Spectral estimation of temporal series at unequal intervals. Computers and Biomedical Research. 19(3). 203–212. 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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