Nathan Lambert

747 citations
23 papers · 183 · h-index 6

Impact in

Papers in

    • Reinforcement Learning in Robotics 5
    • Evolutionary Algorithms and Applications 1
    • Metaheuristic Optimization Algorithms Research 1
    • Ethics and Social Impacts of AI 3

Nathan Lambert

20 papers receiving 171 citations

Peers

Nathan Lambert
Comparison fields: 5 of 60
  • Health Informatics 6
  • Safety Research 24
  • Artificial Intelligence 47
  • Aerospace Engineering 27
  • Computer Science Applications 5
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Citations per field
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Citations per year

Countries citing papers authored by Nathan Lambert

Since Specialization
Citations

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

Fields of papers citing papers by Nathan Lambert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Nathan Lambert, 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 Nathan Lambert Line = papers co-authored together Nathan Lambert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201855
2 202031
3 201023
4 202317
5 202112
6
Debt Begets Debt: Examining Negative Credit Card Behaviors and Other Forms of Consumer Debt
20136
7 20196
8 20105
9
Objective Mismatch in Model-based Reinforcement Learning
20204
10 20254
11 20213
12
On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
20213
13 20233
14 20243
15 20202
16 20212
17 20231
18 20251
19 20231
20 20251

About Nathan Lambert

Nathan Lambert is a scholar working on Artificial Intelligence, Safety Research, Developmental and Educational Psychology, Computer Science Applications and Control and Systems Engineering, having authored 23 papers that have together received 183 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Ethics and Social Impacts of AI (3 papers), Educational and Psychological Assessments (2 papers), Evolutionary Algorithms and Applications (1 paper), Modular Robots and Swarm Intelligence (1 paper), Micro and Nano Robotics (1 paper), Advanced Multi-Objective Optimization Algorithms (1 paper) and Metaheuristic Optimization Algorithms Research (1 paper). The work is most often cited by research in Health Informatics (6 citations), Safety Research (24 citations), Artificial Intelligence (47 citations), Aerospace Engineering (27 citations) and Computer Science Applications (5 citations). Nathan Lambert has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Kristofer S. J. Pister, Daniel Drew, Roberto Calandra, Tom Zick, Franziska Meier, Thomas Krendl Gilbert, Sarah Dean, Akshara Rai, Tianyu Li and Andy Miller. Their work appears in journals such as IEEE Robotics and Automation Letters, Acta Astronautica, British Journal of Educational Psychology, Educational and Child Psychology and Educational Psychology in Practice.

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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