IEEE CASS RJ Chapter Lecture – Machine Learning meets Circuits and Systems

This talk explores how the Machine Learning (ML) and Circuits & Systems (CAS) fields can mutually benefit from one another. We begin with an overview of key ML concepts and their underlying computational and architectural requirements. Next, we discuss how advances in CAS have enabled the widespread deployment of ML systems, emphasizing the role of Approximate Computing, Dataflow Architectures, and Neural Network Compression as essential enablers of energy efficient implementations. We conclude by highlighting ongoing challenges and open research directions at the intersection of ML and CAS.
Speaker(s): Mateus Grellert
Room: bloco H, sala 322, Centro de Tecnologia da UFRJ, Cidade Universitária, Centro de Tecnologia, Rio de Janeiro, Rio de Janeiro, Brazil, 21941972