Gabriel Iturra-Bocaz

Engineer and Master in Computer Science from the Department of Computer Science (DCC) of the Universidad de Chile. His area of expertise focuses on Machine Learning, with a strong emphasis on Natural Language Processing (NLP), Continual Learning, and Data Stream Mining. His thesis, titled “RiverText: A Framework for Training and Evaluating Incremental Word Embeddings from Text Data Streams,” explores the study and implementation of algorithms for text representation within the Continual Learning paradigm.

His outstanding contributions include the publication of a paper based on his work at the SIGIR 2023 conference. In addition, Gabriel has developed an open-source library (https://dccuchile.github.io/rivertext/) that replicates his research findings. This library remains active and continues to evolve, with new features constantly being added and a growing user community.

He currently works as a part-time instructor for the Data Science Laboratory course at the Universidad de Chile.