Marley Maria Bernardes Rebuzzi Vellasco

Marley Vellasco is a Full Professor at the Department of Electrical Engineering at the Pontifical Catholic University of Rio de Janeiro (PUC-Rio), where she joined in 1989. Marley holds a degree in Electrical Engineering/Electronics from PUC-Rio (1984), a Master's in Electrical Engineering from PUC-Rio (1987) and a PhD in Computer Science from University College London (UCL) (1992). She has published over 90 papers in peer-reviewed journals and over 400 full papers in conference proceedings. She has also authored 19 book chapters and 5 books. She has supervised over 100 Master's dissertations and more than 50 doctoral theses. She serves on the Editorial Boards of leading journals in the field of Computational Intelligence, such as Neural Networks, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Artificial Intelligence, IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Cybernetics and Engineering Applications of Artificial Intelligence. Since 2011, she has been a member of the Board of Governors of the International Neural Network Society (INNS), currently serving as the INNS Secretary. She was the Vice-President for Conferences of the IEEE Computational Intelligence Society (CIS) from 2020 to 2023 and is currently an elected member of the IEEE CIS Administrative Committee. Since 1991, she has participated in more than 50 research projects, coordinating over 30 of them, including several international collaborations. She is the coordinator of the Rio de Janeiro Artificial Intelligence Centre (CIA-Rio), sponsored by FAPERJ, and has been awarded the Cientista do Nosso Estado grant since 2008. She has experience in the areas of Electrical Engineering and Computer Science, with emphasis on Computational Intelligence. Her main interests include neural networks, fuzzy logic and evolutionary computing, with a focus on developing intelligent hybrid systems for AutoML (Automated Machine Learning), such as neuro-evolutionary, fuzzy-evolutionary models and neural architecture search (NAS). (Source: Lattes Curriculum)