AI Transformation in Analog Systems

MTL Seminar Series
Wenjie Lu, Analog Devices
RLE Combined (36-462 and 36-428)
Open to
MIT Community

Join members of the MIT, MTL, and AI Hardware Program communities for a
Joint MTL/AI Hardware Program Seminar


Abstract: Artificial Intelligence (AI) is transforming almost every field of technology, and there is no exception for analog systems. Analog Devices has heavily invested in AI transformation, not only creating hardware for AI with world’s lowest power NN accelerator, but also bringing AI to solve the most challenging problems in analog systems.  

In this talk, we will introduce how ADI leverages AI-for-Hardware to tackle challenges in complex analog systems beyond the reach of traditional algorithms. With advancements in AI-for-Hardware, the AI transformation unleashes new possibilities in design, optimization, and testing of future analog systems. We are excited to ignite discussions and explore new research opportunities through the MIT AI Hardware Initiative. 

Wenjie Liu, Analog

Bio: Wenjie Lu is a lead research scientist at Analog Garage at Boston, the internal incubator of Analog Devices Inc. Prior to joining ADI, he received Master and Ph.D. degrees in Electrical Engineering and Computer Science from MIT in 2014 and 2018, respectively. His research focuses on efficient ML algorithms, and applications of ML in real-world problems such as wireless communication and mixed-signal systems.