Gabriel Iturra-Bocaz

Engineer and Master of Science in Computer Science from the Department of Computer Science (DCC) at the University of Chile. His area of expertise focuses on Machine Learning, with a strong emphasis on Natural Language Processing (NLP), Continuous Learning, and Stream Data Mining. His thesis, entitled "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 Continuous Learning paradigm.

His notable contributions include the publication of an article 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 the constant addition of new features and a growing user community.

He currently works as a part-time professor in the Data Science Laboratory course at the University of Chile.