David Isele

1.0k citations
37 papers · 280 · h-index 10

Impact in

Papers in

    • Autonomous Vehicle Technology and Safety 13
    • Transportation and Mobility Innovations 5
    • Vehicle Dynamics and Control Systems 2
    • Reinforcement Learning in Robotics 11
    • AI-based Problem Solving and Planning 2

David Isele

32 papers receiving 270 citations

Peers

David Isele
Comparison fields: 5 of 56
  • Automotive Engineering 106
  • Artificial Intelligence 131
  • Computer Vision and Pattern Recognition 80
  • Control and Systems Engineering 83
  • Safety, Risk, Reliability and Quality 15
Replace Shalin Mehta with:
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Citations per field
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Citations per year

Countries citing papers authored by David Isele

Since Specialization
Citations

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

Fields of papers citing papers by David Isele

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Isele, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Isele Line = papers co-authored together David Isele links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202146
2
Using task features for zero-shot knowledge transfer in lifelong learning
201641
3 202220
4 202119
5 202219
6 201914
7 202011
8 202311
9
CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning
202010
10 201910
11 20167
12 20176
13 19766
14 20236
15 20226
16 20245
17 20235
18
To Go or Not to Go: A Case for Q-Learning at Unsignalized Intersections
20175
19 20225
20 20244

About David Isele

David Isele is a scholar working on Automotive Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering and Information Systems, having authored 37 papers that have together received 280 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (13 papers), Reinforcement Learning in Robotics (11 papers), Robotic Path Planning Algorithms (11 papers), Traffic control and management (8 papers), Transportation and Mobility Innovations (5 papers), Advanced Control Systems Optimization (3 papers), Vehicle Dynamics and Control Systems (2 papers) and AI-based Problem Solving and Planning (2 papers). The work is most often cited by research in Automotive Engineering (106 citations), Artificial Intelligence (131 citations), Computer Vision and Pattern Recognition (80 citations), Control and Systems Engineering (83 citations) and Safety, Risk, Reliability and Quality (15 citations). David Isele has collaborated with scholars based in United States, Japan and South Korea. Frequent co-authors include Kikuo Fujimura, Sangjae Bae, Eric Eaton, Mohammad Rostami, Mykel J. Kochenderfer, Jiachen Li, Liting Sun, Masayoshi Tomizuka, Ran Tian and Keuntaek Lee. Their work appears in journals such as IEEE Robotics and Automation Letters, Computers in Biology and Medicine, IEEE Transactions on Control Systems Technology, IEEE Transactions on Robotics and Journal of Artificial Intelligence Research.

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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