Joint ECE and HK EDSSC Chapter Online Seminar Series - A Bottom-Up Approach towards Intelligent Magnetic Memory: from Materials Design and Devices Property to Application Performance
10:00am - 11:30am
https://hkust.zoom.us/meeting/register/tJAvdeiprzIiG9Qk9Zo9exyyUbejPJ8fIpJ3

The key to the recent success of machine learning lies in the power of computing hardware, a huge amount of data to learn from, and bio-inspired algorithms. However, the existing electronics hardware is failing to process and store the ever-growing learning data and algorithm weights in a fast, cheap, and energy-efficient way. The major bottleneck lies in the low speed and high energy cost incurred when data is transferred between memory storage and logic processing units. One promising approach to solving this bottleneck is a high-density on-chip cache based on magnetic memory. However, R&D of new memory materials across academia and industry remain a trial and error process, lacking frameworks that link material-level chemical design, device-level electrical properties, and application-level energy and delay.

In this talk, Dr. Li will talk about his recent works on two bottom-up frameworks that could bridge materials, devices, and applications to guide memory materials, devices, and circuits research in the future.

讲者/ 表演者:
Dr. Xiang (Shaun) Li
Stanford University

Dr. Li received his Ph.D. degree in Electrical and Computer Engineering from UCLA in 2018, and his B.S. degree in Physics from Peking University, China in 2013. He is now a postdoctoral scholar at Stanford University jointly with Electrical Engineering and Materials Science and Engineering. He is interested in novel materials and devices for non-volatile memory and neuromorphic applications. He has authored magnetic devices chapter of the IEEE Industry Roadmap for Devices and Systems (IRDS) and published 30+ papers with 1000+ citations in Nature Communications, Nano Letters, IEEE, PRL, MRS Bulletin etc.
Dr. Li also has extensive experience in entrepreneurship. He acted as the CTO at Inston Inc., an NSF-funded memory startup from 2018 to 2019. In 2020, he was selected into the Stanford Ignite Certificate Program in Innovation and Entrepreneurship at Stanford University Graduate School of Business.

语言
英文
适合对象
教职员
研究生
主办单位
电子及计算器工程学系
联系方法

Prof. Qiming Shao (e-mail : eeqshao@ust.hk)

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