Bradley C. Love
Scholar

Bradley C. Love

Google Scholar ID: H8dnlegAAAAJ
Senior Research Scientist, Los Alamos National Laboratory. Former utexas.edu and ucl.ac.uk prof.
AI for scientific discoverydeep learningcomputational neurosicencehuman-machine teaming
Citations & Impact
All-time
Citations
6,482
 
H-index
40
 
i10-index
92
 
Publications
20
 
Co-authors
12
list available
Resume (English only)
Academic Achievements
  • 2025 (in press): Published in Patterns on confidence-weighted integration of human and machine judgments
  • 2025 (in press): Published in Nature Communications on adaptive stretching of representations across brain regions and deep learning layers
  • 2025: Published in Journal of Big Data on leakage scenarios in supervised machine learning
  • 2025: Published on arXiv on probability consistency in large language models
  • 2025: Published in Scientific Reports on coordinating multiple mental faculties during learning
  • 2024: Published in Nature Human Behaviour showing LLMs surpass human experts in predicting neuroscience results
  • 2024: Published in Trends in Cognitive Sciences on the benefits and drawbacks of unsupervised learning
  • 2024: Published in eLife on the inevitability and superfluousness of cell types in spatial cognition
  • 2024: Published in Trends in Cognitive Science on 'The Dimensions of Dimensionality'
Research Experience
  • Senior Research Scientist, Los Alamos National Laboratory
  • Professor, University of Texas at Austin
  • Professor, University College London
  • Fellow, The Alan Turing Institute
  • Fellow, European Lab for Learning & Intelligent Systems (ELLIS)
  • Leading the BrainGPT project on applying LLMs to scientific discovery
Background
  • Senior research scientist at Los Alamos National Laboratory
  • Former professor at University of Texas at Austin and University College London
  • Former fellow at The Alan Turing Institute and the European Lab for Learning & Intelligent Systems (ELLIS)
  • Research focuses on cognitive science and computational neuroscience
  • Recently interested in applying modern AI techniques, especially large language models, to accelerate scientific discovery through the BrainGPT project