Zhuo Su
PhD
University of Oulu
Learning compact and efficient feature representations

Energy efficient sensing and computing is vital at all levels, from the smallest sensor like the chip to ultra high performance processors and systems like the cloud, especially in the post Moore's Law era. Energy efficient AI enables AI to move beyond the cloud and to reach the edge, which is critical to the progress of advancing AI and making AI ubiquitous over the next decade. Developing efficient, yet hardware-friendly algorithms such as deep network compression and efficient neural architecture search is essential to enable energy efficient AI.

Track:
Academic Track
PhD Duration:
October 1st, 2018 - December 31st, 2022
First Exchange:
October 1st, 2021 - March 31st, 2022
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