Joseph Modayil

28 papers receiving 1.8k citations

Hit Papers

Rainbow: Combining Improvements in Deep Reinforcement Lea...20182026202020232018250500750

Peers

Joseph Modayil
Comparison fields: 5 of 107
  • Artificial Intelligence 906
  • Computer Vision and Pattern Recognition 554
  • Aerospace Engineering 351
  • Control and Systems Engineering 341
  • Electrical and Electronic Engineering 297
Replace David Meger with:
David Meger Canada
Geoff Gordon United States
Matteo Hessel United Kingdom
Bilal Piot United Kingdom
Dan Horgan United Kingdom
Will Dabney United States
Edward Tunstel United States
Todd Hester United States
Cheng‐Jian Lin Taiwan
Wee Sun Lee Singapore
Joseph Modayil relative to David Meger Canada David Meger's profile →
Citations per field
00.5×1.5×
David Meger · 1×
Citations per year

Countries citing papers authored by Joseph Modayil

Since Specialization
Citations

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

Fields of papers citing papers by Joseph Modayil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joseph Modayil

This figure shows the co-authorship network connecting the top 25 collaborators of Joseph Modayil. A scholar is included among the top collaborators of Joseph Modayil 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 Joseph Modayil. Joseph Modayil 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
#WorkIndexed citations
1
Natural Value Approximators: Learning when to Trust Past Estimates
0
2 146
3
Universal Option Models
8
4
Prediction Driven Behavior: Learning Predictions that Drive Fixed Responses
6
5 7
6 0
7 123
8
Learning Grounded Communicative Intent from Human-Robot Dialog
3
9 12
10 88
11
Integrating Sensing and Cueing for More Effective Activity Reminders
20
12 32
13
Autonomous development of a grounded object ontology by a learning robot
35
14
Where Do Actions Come From? Autonomous Robot Learning of Objects and Actions.
5
15
Integrating Multiple Representations of Spatial Knowledge for Mapping, Navigation, and Communication
25
16 18
17 10
18 38
19 143
20 8

About Joseph Modayil

Joseph Modayil is a scholar working on Artificial Intelligence, Geography, Planning and Development and Signal Processing, having authored 30 papers that have together received 1.9k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (11 papers), Evolutionary Algorithms and Applications (5 papers) and Robot Manipulation and Learning (4 papers). The work is most often cited by research in Artificial Intelligence (906 citations), Computer Vision and Pattern Recognition (554 citations) and Automotive Engineering (177 citations). Joseph Modayil has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Benjamin Kuipers, David Silver, Tom Schaul, Will Dabney, Georg Ostrovski, Matteo Hessel, Mohammad Gheshlaghi Azar, Bilal Piot, Hado van Hasselt and Dan Horgan. Their work appears in journals such as Pattern Recognition, The International Journal of Robotics Research and Robotics and Autonomous Systems.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026