Justin N. Wood
Neuroscience · Indiana University
Publications
108
Citations
2,562
Est. group size
—
Recurring co-author estimate
Active years
32
Publishing since 1995
Justin N. Wood studies how visual intelligence and object recognition develop, comparing how newborn animals (such as chicks and fish) and artificial neural networks learn to see and behave. The work uses controlled-rearing experiments alongside 'digital twin' computer models to explore how much of perception comes from innate structure versus experience (the nature-nurture question). A central goal is reverse-engineering the origins of visual and social intelligence in both biological and machine systems.
Publication activity has been fairly steady over the past decade, averaging around five to eight papers per year, with lower counts in the most recent years likely reflecting incomplete records.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- Transformers self-organize like newborn visual systems when trained in prenatal worlds
arXiv (Cornell University) · 2026
- Transformers self-organize like newborn visual systems when trained in prenatal worlds
arXiv (Cornell University) · 2026
- Computational origins of shape perception
PLoS Computational Biology · 2025
- Artificial intelligence tackles the nature–nurture debate
Nature Machine Intelligence · 2024
- Parallel development of social behavior in biological and artificial fish
Nature Communications · 2024
- Digital Twin Studies for Reverse Engineering the Origins of Visual Intelligence
Annual Review of Vision Science · 2024
- Quantifying convergence and consistency
European Journal of Neuroscience · 2024
- Author response for "Quantifying convergence and consistency"
2024
- Parallel development of object recognition in newborn chicks and deep neural networks
PLoS Computational Biology · 2024
- The Development of Object Recognition Requires Experience with the Surface Features of Objects
Animals · 2024
- Object permanence in newborn chicks is robust against opposing evidence
arXiv (Cornell University) · 2024
- Parallel development of social preferences in fish and machines
arXiv (Cornell University) · 2023
- Quantifying convergence and consistency
2023
- Quantifying convergence and consistency
2023
- Surface Navigation of Alginate Artificial Cells in Mucus Solutions
2023
- arXiv (Cornell University)×11
- Cognition×2
- Cognitive Science×2
- PLoS Computational Biology×2
- Human Brain Mapping×2
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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