Speaker: Mohsen Imani (Ph.D. candidate, Department of Computer Science and Engineering at UC San Diego)

Title: Learning with Brain Efficiency

Abstract: Today's computing systems are facing significant issues in performing learning tasks. In this talk, we show the potential of emerging technologies in designing an energy efficient brain-like machine and accelerate the existing deep learning applications. As an alternative to computing with numbers, we present brain-inspired hyperdimensional (HD) computing that emulates cognition tasks by working with hypervectors. We introduce HD computing as a general computational model that performs a wide range of learning tasks on processing in-memory architecture. We show how this architecture can be used to accelerate deep learning and other big data applications.Bio: Mohsen Imani is a Ph.D. candidate in the Department of Computer Science and Engineering at UC San Diego. His research interests are in brain-inspired computing and computer architecture. He is an author of more than 85 publications at top tier conferences and journals. He has gotten several awards during his study including the outstanding graduate student at CS department, outstanding research award and the best leadership award in the school of engineering at UCSD. Mohsen will be in the academic job market next year.