ITTOO Ashwin

A. ITOO (2)

ITTOO Ashwin

NLP Professor, ULiege

Dr. Ashwin Ittoo is a full professor of Information Systems (Analytics/NLP/Machine Learning) at the University of Liège in Belgium. His main research area is in NLP, specifically, on minimally-supervised or unsupervised algorithms for semantic relation extraction. His research terms develop various machine learning and sophisticated econometrics methods, such including Deep Learning, Lasso and Ridge regressions, which are applied to diverse domains, such as finance and marketing. Currently, he is working on Machine Translation with researchers from the Japan Advanced Institute of Science & Technology and is increasingly interested in AI&Law, particularly, with regards to algorithmic bias and algorithmic collusion and the integration of machine learning and game theory. In addition to his scientific research activities, he maintains close ties with the industrial sector such as by providing consultancy services, conducting industry-sponsored research and supervising PhD and masters students, and delivering keynotes on specialized topics.

Among his other activities, Prof. Ittoo is an Associate Editor (NLP, Machine Learning) of the Elsevier Journal, Computers in Industry (, and has served as guest-editor for several special issues of the Elsevier Journal, Data and Knowledge Engineering ( In addition, he has served/serves as Programme Committee Chair and Organization Chair of numerous conferences in the past.

He obtained his PhD in 2012 from the University of Groningen, The Netherlands, and his masters and bachelors degree from the Nanyang Technological University, Singapore and the National University of Singapore.


ID Event Name Duration Start Date
Algorithmic collusion and the EU’s AI Regulation proposal: living apart together 0 Days June 7, 2021
LCII Brown Bag Seminar series 0 Days February 15, 2019

Liege Competition and Innovation Institute
University of Liege (ULg)
Quartier Agora
Place des Orateurs, 1, Bât. B 33
BE-4000 Liege

Phone: +32 4 366.31.30
Fax: +32 4 366.31.55