Reserach

My research focuses on the intersections between hardware, algorithms, and security in the Machine Learning world. I am generally interested in making Machine Learning systems fast, reliable and efficient. Some of my research topics include:

• How do novel hardware architectures improve the efficiency of running ML workloads?
• How to tweak current ML algorithms to make them more efficient on today and future hardware systems? ML security-related topics with a hardware spin.
• What should the next-generation data-orientated learning system look like?

See advice for students (this includes internships, undergraduate or master projects, and PhD applicants), and information for collaborators, if you want to contact me for study or collaborations.

I lead the DeepWok Lab, and most of the research related updates are in the lab wiki.

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