Fabio Pardo

1.4k citations
5 papers · 175 indexed · h-index 3
Topics
Reinforcement Learning in Robotics (5 papers)Evolutionary Algorithms and Applications (2 papers)Artificial Intelligence in Games (2 papers)
Journals
Spiral (Imperial College London)arXiv (Cornell University)International Conference on Machine Learning

In The Last Decade

Fabio Pardo

5 papers receiving 174 citations

Peers

Fabio Pardo
Comparison fields: 5 of 51
  • Computer Networks and Communications 64
  • Artificial Intelligence 62
  • Electrical and Electronic Engineering 50
  • Control and Systems Engineering 29
  • Computer Vision and Pattern Recognition 26
Replace Christophe Gransart with:
Christophe Gransart France
Zhen Gao China
Marcus Nolte Germany
Raj Rajkumar United States
Shaila Afrin Bangladesh
Ilge Akkaya United States
Felix Dobslaw Sweden
Lucas Wanner Brazil
Simon Fürst Germany
Faisal Tariq United Kingdom
Fabio Pardo relative to Christophe Gransart France Christophe Gransart's profile →
Citations per field
00.5×1.5×
Christophe Gransart · 1×
Citations per year

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

5 of 5 papers shown
#WorkIndexed citations
1
CoMic: Complementary Task Learning & Mimicry for Reusable Skills
5
2 2
3
Q-map: a Convolutional Approach for Goal-Oriented Reinforcement Learning
1
4 163
5 4

About Fabio Pardo

Fabio Pardo is a scholar working on Artificial Intelligence, Developmental and Educational Psychology and Control and Systems Engineering, having authored 5 papers that have together received 175 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Evolutionary Algorithms and Applications (2 papers) and Artificial Intelligence in Games (2 papers). The work is most often cited by research in Computer Networks and Communications (64 citations), Artificial Intelligence (62 citations) and Software (5 citations). Fabio Pardo has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Petar Kormushev, Josh Merel, Raia Hadsell, Leonard Hasenclever and Nicolas Heess. Their work appears in journals such as Spiral (Imperial College London), arXiv (Cornell University) and International Conference on Machine Learning.

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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