Painel do participante 
Biografia do Palestrante:
Bruno Ribeiro is an associate professor in the Department of Computer Science at Purdue University. He obtained his PhD at the University of Massachusetts, Amherst and did his postdoctoral studies at Carnegie Mellon University. His research interests are in invariant & causal representation learning, with a focus on sampling and modeling relational and temporal data. He received an NSF CAREER award in 2020, an Amazon Research Award in 2022, and multiple best paper awards including the ACM SIGMETRICS 2016 best paper award.
22 de Maio, 08:00
23 de Maio, 18:00
Hotel Royal Tulip Brasilia Alvorada Agenda do Palestrante:
Bruno Ribeiro , Daniela Brauner, Diogo Cortiz , Nina da Hora
Antonio Augusto de A. Rocha (Universidade Federal Fluminense), Bruno Ribeiro , Damla Turgut (University of Central Florida)
The use of AI/ML in computer networks is not a new concept, with research dating back more than 20 years. However, recent advancements in tools and techniques have sparked renewed interest in the application of AI/ML in networks. Innovative solutions leveraging AI/ML can now be applied to both traditional and new problems. However, this increased attention has also led to inflated expectations and potential misapplication of AI/ML in computer networks. This panel aims to dispel myths and discuss facts and the future of AI/ML in the field. The discussion will focus on identifying challenges and outlining viable steps for progress.
O uso de AI/ML em redes de computadores não é um conceito
novo, com pesquisas que datam de mais de 20 anos. No entanto, avanços recentes
em ferramentas e técnicas despertaram um interesse renovado na aplicação de
AI/ML em redes. Soluções inovadoras que utilizam IA/ML agora podem ser
aplicadas a problemas novos e tradicionais. No entanto, essa maior atenção
também levou a expectativas infladas e a possíveis aplicações incorretas de
IA/ML em redes de computadores. Este painel visa dissipar mitos e discutir
fatos e o futuro da IA/ML na área. A discussão se concentrará na identificação
de desafios e no esboço de passos viáveis para o progresso.
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