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EliteSenior

Peter Dayan

Max Planck Institute for Biological Cybernetics

DE

Core Metrics

Total Citations

87,112

H-Index

117

Publications

998

i10-Index

383

2-Year Citedness

4.5

avg citations per work

Ability Dimensions

Overall Score58
Prolific
Impact94%

87,112 citations, h=117

Momentum52%

2yr mean: 4.5

Output94%

998 papers (24.9/year)

Efficiency65%

87 cites/paper

Novelty22%

3 unique research topics

Breadth40%

4 topic areas

Peak Power39%

Top 3 papers: 25% of citations

* Percentile scores are calculated relative to all scholars in the computational neuroscience dataset. Tags are assigned based on dimension combinations. Hover over the radar chart for details.

Scholar Profile Analysis

Peter Dayan is a elite scholar with 50k+ citations in computational neuroscience, currently affiliated with Max Planck Institute for Biological Cybernetics.

Over a 40-year academic career, published 998 papers (averaging 24.9 per year), with 87,112 citations.

With an h-index of 117, one of the rare scholars to reach this level, indicating lasting and broad research impact.

Academic impact accumulated gradually: first 5 years account for only 0.1%, indicating later works are more influential.

Primary research areas include Psychology, Psychology, Neuroscience.

Key Findings

Signature Work

"A Neural Substrate of Prediction and Reward" is the most influential work, with 9,324 citations, published in 1997.

Sustained Growth

Very low early citation share indicates influence built through long-term accumulation, with later works being more impactful.

Early Career Analysis (First 5 Years)

Career Start

1985 - 1989

Early Citations

87

Early Works

11

Early Impact %

0.1%

Top Early Career Paper

Semiconductor waveguides: analysis of optical propagation in single rib structures and directional couplers

Publication Timeline

Research Topics

Psychology37.8%
Psychology56.4%
Neuroscience70.2%
Cognition43.6%

Top Publications

11997Science

A Neural Substrate of Prediction and Reward

9,324

Citations

21992Machine Learning

Q-learning

8,791

Citations

31992Machine Learning

Technical Note: Q-Learning

3,585

Citations

Impact Classification

顶级影响力

总引用超过5万次,属于领域顶级学者

持续产出

h-index超过100,表明长期高质量产出

高产学者

发表超过998篇论文,产出极为丰富