Core Metrics
Total Citations
64,014
H-Index
58
Publications
158
i10-Index
109
2-Year Citedness
74.7
avg citations per work
Ability Dimensions
64,014 citations, h=58
2yr mean: 74.7
158 papers (6.6/year)
405 cites/paper
2 unique research topics
4 topic areas
Top 3 papers: 48% 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
Timothy Lillicrap is a elite scholar with 50k+ citations in computational neuroscience, currently affiliated with Google (United States).
Over a 24-year academic career, published 158 papers (averaging 6.6 per year), with 64,014 citations.
An h-index of 58, well above field average, indicates a substantial body of highly-cited work.
Academic impact accumulated gradually: first 5 years account for only 0.1%, indicating later works are more influential.
Primary research areas include Perplexity, Embodied cognition, Embodied cognition.
Key Findings
Signature Work
"Mastering the game of Go with deep neural networks and tree search" is the most influential work, with 15,219 citations, published in 2016.
Consistent Output
Averaging 405 citations per paper, maintaining steady high-quality output.
Sustained Impact
Two-year mean citedness of 74.7 indicates research continues to generate significant impact.
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
2001 - 2005
Early Citations
46
Early Works
1
Early Impact %
0.1%
Top Early Career Paper
Double-stranded RNA as a Not-self Alarm Signal: to Evade, most Viruses Purine-load their RNAs, but some (HTLV-1, Epstein-Barr) Pyrimidine-load
Publication Timeline
Research Topics
Top Publications
Mastering the game of Go with deep neural networks and tree search
15,219
Citations
Mastering the game of Go without human knowledge
8,806
Citations
Continuous control with deep reinforcement learning
6,768
Citations
Continuous control with deep reinforcement learning
5,334
Citations
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
3,322
Citations
Grandmaster level in StarCraft II using multi-agent reinforcement learning
3,236
Citations
Asynchronous Methods for Deep Reinforcement Learning
1,690
Citations
Impact Classification
顶级影响力
总引用超过5万次，属于领域顶级学者
稳定产出
h-index超过50，具有持续的学术产出能力