Fabio Pardo

1.4k total citations
5 papers, 175 citations indexed

About

Fabio Pardo is a scholar working on Artificial Intelligence, Control and Systems Engineering and Sociology and Political Science. According to data from OpenAlex, Fabio Pardo has authored 5 papers receiving a total of 175 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 1 paper in Control and Systems Engineering and 1 paper in Sociology and Political Science. Recurrent topics in Fabio Pardo's work include Reinforcement Learning in Robotics (5 papers), Evolutionary Algorithms and Applications (2 papers) and Artificial Intelligence in Games (2 papers). Fabio Pardo is often cited by papers focused on Reinforcement Learning in Robotics (5 papers), Evolutionary Algorithms and Applications (2 papers) and Artificial Intelligence in Games (2 papers). Fabio Pardo collaborates with scholars based in United Kingdom, United States and Italy. Fabio Pardo's co-authors include Petar Kormushev, Josh Merel, Raia Hadsell, Leonard Hasenclever and Nicolas Heess and has published in prestigious journals such as Spiral (Imperial College London), arXiv (Cornell University) and International Conference on Machine Learning.

In The Last Decade

Fabio Pardo

5 papers receiving 174 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fabio Pardo United Kingdom	3	64	62	50	29	26	5	175
Pradeep B. Mane India	9	70 1.1×	59 1.0×	84 1.7×	24 0.8×	39 1.5×	45	251
Shaila Afrin Bangladesh	4	87 1.4×	62 1.0×	34 0.7×	21 0.7×	17 0.7×	10	243
Zhen Gao China	9	58 0.9×	79 1.3×	99 2.0×	34 1.2×	43 1.7×	56	245
Lanfranco Zanzi Spain	10	210 3.3×	55 0.9×	118 2.4×	23 0.8×	23 0.9×	22	295
Yong-Geun Hong South Korea	8	223 3.5×	107 1.7×	75 1.5×	33 1.1×	27 1.0×	47	292
Saiful Izwan Suliman Malaysia	10	64 1.0×	37 0.6×	151 3.0×	50 1.7×	22 0.8×	53	265
Raj Rajkumar United States	7	109 1.7×	18 0.3×	64 1.3×	29 1.0×	41 1.6×	11	203
Ganesh Gopal Devarajan India	12	154 2.4×	102 1.6×	41 0.8×	34 1.2×	29 1.1×	26	289
Tong Tang China	9	127 2.0×	69 1.1×	69 1.4×	22 0.8×	50 1.9×	42	268
Gereon Weiß Germany	10	47 0.7×	85 1.4×	17 0.3×	28 1.0×	12 0.5×	34	203

Countries citing papers authored by Fabio Pardo

Since Specialization

Citations

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

Fields of papers citing papers by Fabio Pardo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabio Pardo

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

All Works

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5 of 5 papers shown

1.

Hasenclever, Leonard, Fabio Pardo, Raia Hadsell, Nicolas Heess, & Josh Merel. (2020). CoMic: Complementary Task Learning & Mimicry for Reusable Skills. International Conference on Machine Learning. 4105–4115. 5 indexed citations

2.

Pardo, Fabio, et al.. (2020). Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 5355–5362. 2 indexed citations

3.

Pardo, Fabio, et al.. (2018). Q-map: a Convolutional Approach for Goal-Oriented Reinforcement Learning. Spiral (Imperial College London). 1 indexed citations

4.

Pardo, Fabio, et al.. (2018). Action Branching Architectures for Deep Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 163 indexed citations

5.

Pardo, Fabio, et al.. (2017). Action Branching Architectures for Deep Reinforcement Learning. arXiv (Cornell University). 32(1). 4131–4138. 4 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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