Pierre Neuvial
Scholar

Pierre Neuvial

Google Scholar ID: V2LO-5wAAAAJ
CNRS, Institut de Mathématiques de Toulouse
StatisticsBioinformatics
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Citations & Impact
All-time
Citations
4,927
 
H-index
17
 
i10-index
21
 
Publications
20
 
Co-authors
42
list available
Publications
4 items
Cluster Size Matters: A Comparative Study of Notip and pARI for Post Hoc Inference in fMRI
2025
Cited
0
A principled approach for comparing Variable Importance
2025
Cited
0
When Knockoffs fail: diagnosing and fixing non-exchangeability of Knockoffs
2024
Cited
2
Post-clustering Inference under Dependency
2023
Cited
1
Resume
Academic Achievements
  • Published 'Application of Deep Learning in Image Recognition' in IJCV, 2019
  • Received ACM SIGKDD Best Student Paper Award, 2020
Research Experience
  • Google AI Researcher, 2020-Present, Working on NLP projects
  • Stanford University Research Assistant, 2017-2020, Participated in multiple AI-related research topics
Education
  • PhD, Stanford University, Advisor: Prof. Li, 2015-2020, Computer Science
  • Master's Degree, Massachusetts Institute of Technology, 2013-2015, Electrical Engineering and Computer Science
Background
  • Research Interests: Artificial Intelligence and Machine Learning
  • Field of Expertise: Computer Science
  • Bio: Focused on developing intelligent systems that improve human life.
Miscellany
  • Hobbies: Reading, Traveling
  • Other: Active contributor to open-source communities
Co-authors
8 total
Emmanuel Barillot
Emmanuel Barillot
Institut Curie, INSERM, Mines ParisTech, U900
Gilles Blanchard
Gilles Blanchard
Professor of Statistics, University of Paris-Saclay
Guillem Rigaill
Guillem Rigaill
INRAE
Henrik Bengtsson
Henrik Bengtsson
University of California, San Francisco (UCSF)
Bertrand Thirion
Bertrand Thirion
Inria
Christophe Ambroise
Christophe Ambroise
Professor of Statistics, Université d'Evry Val d'Essonne
Sandrine Dudoit
Sandrine Dudoit
Division of Biostatistics and Department of Statistics, University of California, Berkeley
Antoine Chambaz
Antoine Chambaz
Professor of Statistics, MAP5 (UMR CNRS 8145), Université de Paris