Tim de Bruin

1.1k total citations · 1 hit paper
9 papers, 737 citations indexed

About

Tim de Bruin is a scholar working on Artificial Intelligence, Management Science and Operations Research and Electrical and Electronic Engineering. According to data from OpenAlex, Tim de Bruin has authored 9 papers receiving a total of 737 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Management Science and Operations Research and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Tim de Bruin's work include Reinforcement Learning in Robotics (8 papers), Advanced Bandit Algorithms Research (4 papers) and Smart Grid Energy Management (3 papers). Tim de Bruin is often cited by papers focused on Reinforcement Learning in Robotics (8 papers), Advanced Bandit Algorithms Research (4 papers) and Smart Grid Energy Management (3 papers). Tim de Bruin collaborates with scholars based in Netherlands, United Kingdom and Romania. Tim de Bruin's co-authors include Robert Babuška, Jens Kober, K. Verbert, Domagoj Tolić, Ivana Palunko, Lucian Buşoniu and Karl Tuyls and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, Journal of Machine Learning Research and IEEE Robotics and Automation Letters.

In The Last Decade

Tim de Bruin

9 papers receiving 713 citations

Hit 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.

Reinforcement learning for control: Performance, stability, and deep approximators

2018 312 citations Lucian Buşoniu, Tim de Bruin et al. Annual Reviews in Control profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tim de Bruin Netherlands	6	368	263	155	127	118	9	737
Sumika Chauhan India	21	417 1.1×	281 1.1×	275 1.8×	162 1.3×	88 0.7×	59	995
Iuliu Alexandru Zamfirache Canada	9	350 1.0×	235 0.9×	85 0.5×	89 0.7×	135 1.1×	10	713
Elena‐Lorena Hedrea Romania	11	308 0.8×	194 0.7×	84 0.5×	75 0.6×	69 0.6×	41	625
Indranil Roychoudhury United States	17	736 2.0×	230 0.9×	125 0.8×	93 0.7×	74 0.6×	65	1.0k
Ahmad Nor Kasruddin Nasir Malaysia	17	420 1.1×	237 0.9×	144 0.9×	95 0.7×	68 0.6×	80	736
Xianfeng Yuan China	15	333 0.9×	360 1.4×	119 0.8×	138 1.1×	95 0.8×	68	875
Kai Zenger Finland	17	496 1.3×	223 0.8×	143 0.9×	506 4.0×	94 0.8×	127	1.0k
Patrice Aknin France	13	161 0.4×	186 0.7×	148 1.0×	141 1.1×	39 0.3×	42	603
Agustín Jiménez Spain	14	273 0.7×	269 1.0×	46 0.3×	90 0.7×	78 0.7×	53	622
Junwei Gao China	15	342 0.9×	198 0.8×	104 0.7×	189 1.5×	47 0.4×	55	726

Countries citing papers authored by Tim de Bruin

Since Specialization

Citations

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

Fields of papers citing papers by Tim de Bruin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim de Bruin. 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 Tim de Bruin. The network helps show where Tim de Bruin may publish in the future.

Co-authorship network of co-authors of Tim de Bruin

This figure shows the co-authorship network connecting the top 25 collaborators of Tim de Bruin. A scholar is included among the top collaborators of Tim de Bruin 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 Tim de Bruin. Tim de Bruin 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:

9 of 9 papers shown

1.

Bruin, Tim de, Jens Kober, Karl Tuyls, & Robert Babuška. (2020). Fine-tuning Deep RL with Gradient-Free Optimization. IFAC-PapersOnLine. 53(2). 8049–8056. 3 indexed citations

2.

Bruin, Tim de. (2019). Sample Efficient Deep Reinforcement Learning for Control. Research Repository (Delft University of Technology). 1 indexed citations

3.

Bruin, Tim de, Jens Kober, Karl Tuyls, & Robert Babuška. (2018). Experience selection in deep reinforcement learning for control. Journal of Machine Learning Research. 19(1). 347–402. 44 indexed citations

4.

Bruin, Tim de, Jens Kober, Karl Tuyls, & Robert Babuška. (2018). Integrating State Representation Learning Into Deep Reinforcement Learning. IEEE Robotics and Automation Letters. 3(3). 1394–1401. 65 indexed citations

5.

Buşoniu, Lucian, Tim de Bruin, Domagoj Tolić, Jens Kober, & Ivana Palunko. (2018). Reinforcement learning for control: Performance, stability, and deep approximators. Annual Reviews in Control. 46. 8–28. 312 indexed citations breakdown →

6.

Bruin, Tim de, Jens Kober, Karl Tuyls, & Robert Babuška. (2016). Off-policy experience retention for deep actor-critic learning. Neural Information Processing Systems. 3 indexed citations

7.

Bruin, Tim de, K. Verbert, & Robert Babuška. (2016). Railway Track Circuit Fault Diagnosis Using Recurrent Neural Networks. IEEE Transactions on Neural Networks and Learning Systems. 28(3). 523–533. 242 indexed citations

8.

Bruin, Tim de, Jens Kober, Karl Tuyls, & Robert Babuška. (2016). Improved deep reinforcement learning for robotics through distribution-based experience retention. Data Archiving and Networked Services (DANS). 3947–3952. 23 indexed citations

9.

Bruin, Tim de, Jens Kober, Karl Tuyls, & Robert Babuška. (2015). The importance of experience replay database composition in deep reinforcement learning. Neural Information Processing Systems. 44 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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