Hosted by Professor Pedram Khalili

CMOS technology has been the mainstream hardware technology for the development of ubiquitous information technology so far. In the era of 'big data' and 'Internet of Things' nowadays, the traditional computing architecture based on CMOS hardware has become increasingly inefficient to support Artificial Intelligence (AI) and Machine Learning (ML), which necessitates some emerging technologies, such as memristive technology. Memristive devices(1) have become a promising candidate to enable bio-inspired computing with much improved efficiency and throughput(2,3). Such computing can be implemented on a Resistive Neural Network(4) with memristive synapses(5) and neurons(6) or a Capacitive Neural Network(7,8) with memcapacitive synapses and neurons. I will first briefly introduce the promises and challenges of memristive materials and devices for those applications and then discuss examples with different levels of bio-inspiration: first, deep learning accelerators(9) with supervised online learning(10); second, neuromorphic computing for pattern classification with unsupervised learning(6); last, other computing applications, such as reinforcement learning(11) for decision making, artificial nociceptors for robotics(12), provable key destruction(13) and true random number generators(14) for cybersecurity.

1 Nature Nanotechnology 8, 13 (2013)

2 Nature materials 18, 309 (2019)

3 Nature Reviews Materials 5, 173 (2020)

4 Nature Machine Intelligence 1, 434 (2019)

5 Nature Materials 16, 101 (2017)

6 Nature Electronics 1, 137 (2018)

7 Nature Communications 9, 3208 (2018)

8 Nature Machine Intelligence 1, 49 (2019)

9 Nature Electronics 1, 52 (2018)

10 Nature communications 9, 2385 (2018)

11 Nature Electronics 2, 115 (2019)

12 Nature communications 9, 417 (2018)

13 Nature Electronics 1, 548 (2018)

14 Nature communications 8, 882 (2017)

J. Joshua Yang is a professor of the Department of Electrical and Computer Engineering at the University of Southern California. He was a professor of the ECE department at the University of Massachusetts Amherst between 2015 and 2020. He spent about 8 years at HP Labs between 2007 and 2015, leading the emerging devices team for memory and computing. His current research interest is Post-CMOS hardware for neuromorphic computing, machine learning and artificial intelligence, where he published several pioneering papers and holds 118 granted and about 60 pending US Patents. He is the Founder Chair of the IEEE Neuromorphic Computing Technical Committee, a recipient of the Powell Faculty Research Award and a recipient of UMass distinguished faculty lecturer and UMass Chancellor's Medal, the highest honor of UMass. He was named as a Spotlight Scholar of UMass Amherst in 2017.He is a Clarivate? Highly Cited Researcher in the field of Cross-Field and serves on the Advisory Boards of a number of prime international journals and conferences.

**This will be a virtual seminar, please use the Zoom link provided in this listing to attend the event.