Max Lungarella

4.3k total citations · 1 hit paper
49 papers, 2.8k citations indexed

About

Max Lungarella is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Max Lungarella has authored 49 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cognitive Neuroscience, 16 papers in Biomedical Engineering and 12 papers in Artificial Intelligence. Recurrent topics in Max Lungarella's work include Neural dynamics and brain function (14 papers), Robotic Locomotion and Control (12 papers) and Robot Manipulation and Learning (11 papers). Max Lungarella is often cited by papers focused on Neural dynamics and brain function (14 papers), Robotic Locomotion and Control (12 papers) and Robot Manipulation and Learning (11 papers). Max Lungarella collaborates with scholars based in Switzerland, Japan and United States. Max Lungarella's co-authors include Rolf Pfeifer, Fumiya Iida, Olaf Sporns, Yasuo Kuniyoshi, Giulio Sandini, Giorgio Metta, Luc Berthouze, Hugo Gravato Marques, Alexandre Pitti and Alejandro Hernández Arieta and has published in prestigious journals such as Science, Trends in Cognitive Sciences and Communications of the ACM.

In The Last Decade

Max Lungarella

49 papers receiving 2.6k citations

Hit Papers

Self-Organization, Embodiment, and Biologically Inspired ... 2007 2026 2013 2019 2007 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Max Lungarella Switzerland 19 1.0k 945 668 607 565 49 2.8k
Koh Hosoda Japan 32 2.0k 2.0× 727 0.8× 1.3k 1.9× 616 1.0× 742 1.3× 247 4.1k
Tony Pipe United Kingdom 25 717 0.7× 608 0.6× 673 1.0× 364 0.6× 489 0.9× 159 2.4k
Nathan F. Lepora United Kingdom 29 1.8k 1.7× 1.8k 1.9× 865 1.3× 422 0.7× 189 0.3× 137 3.1k
Lorenzo Jamone United Kingdom 21 823 0.8× 670 0.7× 649 1.0× 221 0.4× 274 0.5× 84 1.6k
Ali Meghdari Iran 25 648 0.6× 310 0.3× 650 1.0× 173 0.3× 396 0.7× 215 2.4k
Yasuo Kuniyoshi Japan 37 2.6k 2.5× 1.4k 1.5× 2.3k 3.4× 898 1.5× 1.5k 2.6× 318 6.8k
Domenico Campolo Singapore 26 897 0.9× 379 0.4× 471 0.7× 376 0.6× 69 0.1× 145 2.1k
Michael A. Peshkin United States 44 2.5k 2.5× 2.1k 2.2× 1.8k 2.7× 1.7k 2.8× 113 0.2× 195 5.9k
Fumiya Iida United Kingdom 39 4.9k 4.8× 1.2k 1.3× 1.7k 2.5× 2.3k 3.7× 476 0.8× 268 7.0k
Takao Satô Japan 24 507 0.5× 682 0.7× 474 0.7× 190 0.3× 47 0.1× 349 2.6k

Countries citing papers authored by Max Lungarella

Since Specialization
Citations

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

Fields of papers citing papers by Max Lungarella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Max Lungarella

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

All Works

20 of 20 papers shown
1.
Flück, Martin, et al.. (2017). Cardiovascular and Muscular Consequences of Work-Matched Interval-Type of Concentric and Eccentric Pedaling Exercise on a Soft Robot. Frontiers in Physiology. 8. 640–640. 10 indexed citations
2.
Pfeifer, Rolf, Fumiya Iida, & Max Lungarella. (2014). Cognition from the bottom up: on biological inspiration, body morphology, and soft materials. Trends in Cognitive Sciences. 18(8). 404–413. 78 indexed citations
3.
Marques, Hugo Gravato, Steffen Wittmeier, Owen Holland, et al.. (2010). ECCE1: The first of a series of anthropomimetic musculoskeletal upper torsos. BOA (University of Milano-Bicocca). 391–396. 83 indexed citations
4.
Lungarella, Max, et al.. (2010). On the influence of sensor morphology on eye motion coordination. Zurich Open Repository and Archive (University of Zurich). 238–243. 2 indexed citations
5.
Shimizu, Masahiro, Takuma Kato, Max Lungarella, & Akio Ishiguro. (2008). Adaptive Modular Robots Through Heterogeneous Inter-Module Connections. Journal of Robotics and Mechatronics. 20(3). 386–393. 2 indexed citations
6.
Miyashita, Shuhei, et al.. (2008). Tribolon: Water based self-assembly robot with freezing connector (video). 4147–4148. 1 indexed citations
7.
Ishiguro, Katsuhiko, Nobuyuki Otsu, Max Lungarella, & Yasuo Kuniyoshi. (2008). Detecting direction of causal interactions between dynamically coupled signals. Physical Review E. 77(2). 26216–26216. 16 indexed citations
8.
Lungarella, Max, Alexandre Pitti, & Yasuo Kuniyoshi. (2007). Information transfer at multiple scales. Physical Review E. 76(5). 56117–56117. 72 indexed citations
9.
Lungarella, Max. (2007). Developmental robotics. Scholarpedia. 2(8). 3104–3104. 3 indexed citations
10.
Pfeifer, Rolf, Max Lungarella, & Fumiya Iida. (2007). Self-Organization, Embodiment, and Biologically Inspired Robotics. Science. 318(5853). 1088–1093. 832 indexed citations breakdown →
11.
Lungarella, Max & Olaf Sporns. (2006). Mapping Information Flow in Sensorimotor Networks. PLoS Computational Biology. 2(10). e144–e144. 194 indexed citations
12.
Kuniyoshi, Yasuo, et al.. (2006). Adaptive body schema for robotic tool-use. Advanced Robotics. 20(10). 1105–1126. 51 indexed citations
13.
Yokoi, Hiroshi, et al.. (2005). Artificial Whiskers: Structural Characterization and Implications for Adaptive Robots. Journal of Robotics and Mechatronics. 17(5). 584–595. 1 indexed citations
14.
García, Gabriel J., Max Lungarella, & Danesh Tarapore. (2005). Information-theoretic approach to embodied category learning. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 332–337. 3 indexed citations
15.
Lungarella, Max, et al.. (2005). Methods for Quantifying the Informational Structure of Sensory and Motor Data. Neuroinformatics. 3(3). 243–262. 84 indexed citations
16.
Tarapore, Danesh, Max Lungarella, & Gabriel J. García. (2004). Fingerprinting Agent-Environment Interaction via Information Theory. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 6 indexed citations
17.
García, Gabriel J., Max Lungarella, Peter Eggenberger Hotz, Kojiro Matsushita, & Rolf Pfeifer. (2004). Simulating development in a real robot: on the concurrent increase of sensory, motor, and neural complexity. CogPrints (University of Southampton). 14 indexed citations
18.
Lungarella, Max & Luc Berthouze. (2002). On the interplay between morphological, neural and environmental dynamics. 2 indexed citations
19.
Lungarella, Max & Luc Berthouze. (2002). On the Interplay Between Morphological, Neural, and Environmental Dynamics: A Robotic Case Study. Adaptive Behavior. 10(3-4). 223–241. 30 indexed citations
20.
Lungarella, Max. (2001). Robots As Cognitive Tools Information theoretic analysis of sensory-motor data. 16 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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