Maíra Gatti de Bayser

Maira de Bayser portrait
Research Software Engineer

Maíra Gatti de Bayser is a Research Staff Member (RSM) in the Conversational Intelligence group at IBM Research, Brazil. She Joined the Lab in February 2011, when it just started the operations in Rio de Janeiro.

In 2018 Maíra received the 7th patents plateau award. In 2015 Maíra was honoureed with the Best of IBM award.

In 2014, she was nominated Master Inventor, she has won the Outstanding Technical Achievement Award (OTAA) four times.

Her main research areas are Artificial Intelligence and Software Engineering and she is currently working with Dialogue Systems.

At IBM Research, she has lead projects with Machine Learning, Big Data and Real-time Streaming Data.

Maíra holds Ph.D. (2009) and M.Sc. (2006) in Software Engineering for Multi-Agent Systems from Informatics Department of the PUC-Rio, Pontifical Catholic University of Rio de Janeiro, Brazil. She has been a research fellow at the Agent and Intelligent Systems of Kings College London, England (2009), and before a visit student at the University of Waterloo, Canada (2008). During the Ph.D., her research on self-organizing decentralized systems using multi-agent systems arose from the modeling and simulation of the stem cell behavior in cooperation with the Neurogenesis and Cell Differentiation Lab from the Federal University of Rio de Janeiro (UFRJ, Brazil). During the M. Sc, she worked with fault tolerance and open systems.

Prior to IBM Research, Maira worked at the Software Engineering Lab (LES), PUC-Rio (2005-2010) in several projects funded by FINEP and CNPq. She wrote and leaded a project that was funded by CNPq (2007) and she also worked with the Distributed Systems group of Tecgraf Lab, PUC-Rio (2008-2011) to do R&D of fault tolerance for an Enterprise Service Bus to Petrobras, a Brazilian Oil Company.

Focus Area

Multi-Agent Systems, Machine Learning, Neural Networks, NLP, Dialogue Systems, HCI

CISL Projects

CISL Publications


  1. . "HUMAINE: Human Multi-Agent Immersive Negotiation Competition," In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems [Full Paper] [Publication, Abstract]


  1. . "Embodied Conversational AI Agents in a Multi-modal Multi-agent Competitive Dialogue," Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence Demos. Pages 6512-6514 [Publication, Abstract]