ECE Seminar - Neuromorphic computing with memristors
9:30am - 10:30am
https://hkust.zoom.us/j/95423258052 Meeting ID: 954 2325 8052

The rise of memristors as artificial synapses and neurons provides a new approach in developing a neuromorphic hardware. A memristor-based neuromorphic processor would “compute by physics” which uses intrinsic device properties as computing principles and implements circuits and architectures based on biological inspirations. In this talk, I will first introduce the promises and challenges of memristors for neuromorphic computing. I will then discuss our efforts in addressing some fundamental device challenges of memristors and present our new concept in designing memristor computing arrays. Finally, I will conclude my talk with some brief discussions into future research directions.


Biography:


Dr. Peng Lin is a Postdoc Associate in Prof. Jeehwan Kim’s group at Massachusetts Institute of Technology (MIT). He received his PhD in Electrical and Computer Engineering from University of Massachusetts Amherst in 2017. His current research focuses on neuromorphic computing and heterogeneously integrated systems, emphasizing on combining novel nanoelectronics device concept, advanced nanofabrication methods and brain-inspired computing paradigms to build functional neuromorphic hardware towards real-world applications. To date, Dr. Lin has published more than 30 papers in top peer-reviewed journals, such as Nature Electronics, Nature Nanotechnology, Nature Machine Intelligence, etc.

When
Time
9:30am - 10:30am
Where
https://hkust.zoom.us/j/95423258052 Meeting ID: 954 2325 8052
Event Format
Speakers / Performers:
Dr. Peng Lin
Postdoc Associate, Research Laboratory of Electronics, Massachusetts Institute of Technology

Dr. Peng Lin is a Postdoc Associate in Prof. Jeehwan Kim’s group at Massachusetts Institute of Technology (MIT). He received his PhD in Electrical and Computer Engineering from University of Massachusetts Amherst in 2017. His current research focuses on neuromorphic computing and heterogeneously integrated systems, emphasizing on combining novel nanoelectronics device concept, advanced nanofabrication methods and brain-inspired computing paradigms to build functional neuromorphic hardware towards real-world applications. To date, Dr. Lin has published more than 30 papers in top peer-reviewed journals, such as Nature Electronics, Nature Nanotechnology, Nature Machine Intelligence, etc.

Language
English
Recommended For
Faculty and staff
PG students
Organizer
Department of Electronic & Computer Engineering
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