Marco Dinarelli
Scholar

Marco Dinarelli

Google Scholar ID: iPTtYm8AAAAJ
LIG CNRS
Natural Language ProcessingDeep and Machine LearningText CategorizationKnowledge Management
Citations & Impact
All-time
Citations
493
 
H-index
11
 
i10-index
12
 
Publications
20
 
Co-authors
26
list available
Resume (English only)
Academic Achievements
  • July 2, 2025, Session chair (session TALN 3) at the CORIA-TALN 2025 conference; June 24, 2025, Paper accepted at the TSD 2025 international conference; May 19, 2025, Paper accepted at the Interspeech 2025 international conference.
Research Experience
  • January 2019 to present, Researcher at LIG (Laboratoire d'Informatique de Grenoble) in the GETALP group, CNRS; October 2017 to December 2018, Invited researcher at LIG in the GETALP group; October 2013 to December 2018, Permanent researcher at Lattice laboratory (Langues, Textes, Traitements informatiques, Cognition); December 2011 to September 2013, Post-doctoral researcher at the TLP (NLP) group at LIMSI-CNRS, under the direction of François Yvon and in collaboration with Aurélien Max; June 2010 to November 2011, Post-doctoral researcher in the TLP group at LIMSI-CNRS, under the direction of Sophie Rosset.
Education
  • March 2010, Ph.D. in Information and Communication Technology from the ICT International Doctoral School of the Department of Computer Science and Information Engineering (DISI) at the University of Trento; April 2006, Master's degree in Computer Science from the Department of Computer Science of the University of Pisa; December 2003, Bachelor's degree in Computer Science from the same university.
Background
  • Research interests: Machine Learning and Deep Learning, Natural Language Processing (especially sequence modelling), Probabilistic models (such as Neural Networks, Conditional Random Fields, Stochastic Finite State Machines, Support Vector Machines, probabilistic grammars), Structured features design for NLP, Representation learning. Professional field: Coreference resolution, Spoken Language Understanding, Document-Level Neural Machine Translation.