Roi Reichart
Scholar

Roi Reichart

Google Scholar ID: xXJIsh4AAAAJ
Professor of Artificial Intelligence, Technion - Israel Institute of Technology
natural language processingmachine learningartificial intelligencehealth AIAI for Science
Citations & Impact
All-time
Citations
7,167
 
H-index
41
 
i10-index
84
 
Publications
20
 
Co-authors
37
list available
Contact
Resume (English only)
Academic Achievements
  • Editing a special issue titled 'Artificial Intelligence in Alzheimer’s disease and Related Dementias Research: Unveiling Novel Research Directions' in the Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) journal. Paper 'On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs' received the Senior Area Chair best paper award for Model Analysis and Interpretability in NNACL 2025.
Research Experience
  • Active in the hi-tech industry, served as a chief scientist for several companies (e.g., suridata.ai, recently purchased by Fortinet) and provides consultancy services to other companies (among previous companies: Yahoo!, Gong.io, and Meta).
Background
  • Professor and Schmidt Career Advancement Chair in Artificial Intelligence at the faculty of Data and Decisions Science (formerly Industrial Engineering and Management) of the Technion – Israel Institute of Technology. Affiliated lecturer at The Centre for Human-Inspired Artificial Intelligence (CHIA) of the University of Cambridge, UK. Co-editor in Chief of the Transactions of the Association for Computational Linguistics (TACL, MIT Press) and a fellow of ELLIS. Research focuses on out-of-distribution generalization, sample-efficient learning, multilingual natural language processing, multi-modal learning, causality and machine learning/NLP, particularly in the context of large language model explainability, interpretability, and robustness to distributional shifts. Works on developing decision-making agents capable of natural language communication, and harnessing NLP and multi-modal models for scientific and health-related discovery – especially in neuroscience, mental health, cognition, emotion, and behavior.
Miscellany
  • Interest in applying NLP and multi-modal models to scientific and health-related discovery, particularly in fields such as neuroscience, mental health, cognition, emotion, and behavior.