T. Serre Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Researcher

John Brown University

faculty

95 h-index 539 pubs 36,110 cited

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Biography and Research Information

OverviewAI-generated summary

Dr. T. Serre's research spans an unusually broad range of topics, from the fundamental constituents of matter to the complexities of the human brain. While affiliated with John Brown University, Serre actively publishes on diverse subjects, including both theoretical and experimental particle physics, high-energy particle collisions, and advanced particle detector technology. Publications also reveal expertise in neural dynamics, brain function, and quantum chromodynamics. Serre's recent work involves developing explainable AI methods, as seen in research on concept recursive activation factorization. Other projects include harmonizing object recognition strategies in deep neural networks with human perception and creating evaluation frameworks for explainability methods. Also noteworthy is a contribution to plant science through the creation of a vetted image dataset of fossil leaves for machine learning.

Metrics

  • h-index: 95
  • Publications: 539
  • Citations: 36,110

Selected Publications

  • RTify: Aligning Deep Neural Networks with Human Behavioral Decisions (2024) DOI
  • Learning Functional Transduction (2023) DOI
  • Toward modeling visual routines of object segmentation with biologically inspired recurrent vision models (2022) DOI

Collaborators

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